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Reducing overprediction of molecular crystal structures via threshold clustering

Crystal structure prediction is becoming an increasingly valuable tool for assessing polymorphism of crystalline molecular compounds, yet invariably, it overpredicts the number of polymorphs. One of the causes for this overprediction is in neglecting the coalescence of potential energy minima, separ...

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Detalles Bibliográficos
Autores principales: Butler, Patrick W. V., Day, Graeme M.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: National Academy of Sciences 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10266058/
https://www.ncbi.nlm.nih.gov/pubmed/37252993
http://dx.doi.org/10.1073/pnas.2300516120
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author Butler, Patrick W. V.
Day, Graeme M.
author_facet Butler, Patrick W. V.
Day, Graeme M.
author_sort Butler, Patrick W. V.
collection PubMed
description Crystal structure prediction is becoming an increasingly valuable tool for assessing polymorphism of crystalline molecular compounds, yet invariably, it overpredicts the number of polymorphs. One of the causes for this overprediction is in neglecting the coalescence of potential energy minima, separated by relatively small energy barriers, into a single basin at finite temperature. Considering this, we demonstrate a method underpinned by the threshold algorithm for clustering potential energy minima into basins, thereby identifying kinetically stable polymorphs and reducing overprediction.
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spelling pubmed-102660582023-11-30 Reducing overprediction of molecular crystal structures via threshold clustering Butler, Patrick W. V. Day, Graeme M. Proc Natl Acad Sci U S A Physical Sciences Crystal structure prediction is becoming an increasingly valuable tool for assessing polymorphism of crystalline molecular compounds, yet invariably, it overpredicts the number of polymorphs. One of the causes for this overprediction is in neglecting the coalescence of potential energy minima, separated by relatively small energy barriers, into a single basin at finite temperature. Considering this, we demonstrate a method underpinned by the threshold algorithm for clustering potential energy minima into basins, thereby identifying kinetically stable polymorphs and reducing overprediction. National Academy of Sciences 2023-05-30 2023-06-06 /pmc/articles/PMC10266058/ /pubmed/37252993 http://dx.doi.org/10.1073/pnas.2300516120 Text en Copyright © 2023 the Author(s). Published by PNAS. https://creativecommons.org/licenses/by-nc-nd/4.0/This article is distributed under Creative Commons Attribution-NonCommercial-NoDerivatives License 4.0 (CC BY-NC-ND) (https://creativecommons.org/licenses/by-nc-nd/4.0/) .
spellingShingle Physical Sciences
Butler, Patrick W. V.
Day, Graeme M.
Reducing overprediction of molecular crystal structures via threshold clustering
title Reducing overprediction of molecular crystal structures via threshold clustering
title_full Reducing overprediction of molecular crystal structures via threshold clustering
title_fullStr Reducing overprediction of molecular crystal structures via threshold clustering
title_full_unstemmed Reducing overprediction of molecular crystal structures via threshold clustering
title_short Reducing overprediction of molecular crystal structures via threshold clustering
title_sort reducing overprediction of molecular crystal structures via threshold clustering
topic Physical Sciences
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10266058/
https://www.ncbi.nlm.nih.gov/pubmed/37252993
http://dx.doi.org/10.1073/pnas.2300516120
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