Reducing overprediction of molecular crystal structures via threshold clustering
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, 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.
Monte Carlo, crystal structure prediction, energy landscapes, polymorphism
Butler, Patrick W. V.
6e0f7f4a-4cb5-4868-9820-d120c7d905f8
Day, Graeme M.
e3be79ba-ad12-4461-b735-74d5c4355636
6 June 2023
Butler, Patrick W. V.
6e0f7f4a-4cb5-4868-9820-d120c7d905f8
Day, Graeme M.
e3be79ba-ad12-4461-b735-74d5c4355636
Butler, Patrick W. V. and Day, Graeme M.
(2023)
Reducing overprediction of molecular crystal structures via threshold clustering.
Proceedings of the National Academy of Sciences, 120 (23), [e2300516120].
(doi:10.1073/pnas.2300516120).
Abstract
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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Accepted/In Press date: 1 May 2023
e-pub ahead of print date: 30 May 2023
Published date: 6 June 2023
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Funding Information:
ACKNOWLEDGMENTS. P.W.V.B. is funded by a University of Southampton Presidential Scholarship. We acknowledge the Iridis5 High Performance Computing facility, and associated support services at the University of Southampton. Via our membership of the UK’s HEC Materials Chemistry Consortium, which is funded by EPSRC (EP/R029431), this work used the ARCHER2 UK National Supercomputing Service (https://www.archer2.ac.uk).
Publisher Copyright:
Copyright © 2023 the Author(s).
Keywords:
Monte Carlo, crystal structure prediction, energy landscapes, polymorphism
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Local EPrints ID: 479996
URI: http://eprints.soton.ac.uk/id/eprint/479996
ISSN: 0027-8424
PURE UUID: 0e1cf429-2705-4df0-88f2-95ea917b7ae4
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Date deposited: 31 Jul 2023 17:09
Last modified: 17 Mar 2024 03:29
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Author:
Patrick W. V. Butler
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