Convergence properties of crystal structure prediction by quasi-random sampling
Convergence properties of crystal structure prediction by quasi-random sampling
Generating sets of trial structures that sample the configurational space of crystal packing possibilities is an essential step in the process of an ab initio crystal structure prediction (CSP). One effective methodology for performing such a search relies on low-discrepancy, quasi-random sampling, and our implementation of such a search for molecular crystals is described in this paper. Herein we restrict ourselves to rigid organic molecules, and by considering their geometric properties, build trial crystal packings as starting points for local lattice energy minimization. We also describe a method to match instances of the same structure, which we use to measure the convergence of our packing search towards completeness. The use of these tools is demonstrated for a set of molecules with diverse molecular characteristics and as representative of areas of application where CSP has been applied. An important finding is that the lowest energy crystal structures are typically located early and frequently during a quasi-random search of phase space. It is usually the complete sampling of higher energy structures that requires extended sampling. We show how the procedure can first be refined, through targetting the volume of the generated crystal structures, and then extended across a range of space groups to make a full CSP search and locate experimentally observed and lists of hypothetical polymorphs. As the described method has also been created to lie at the base of more involved approaches to CSP, which are being developed within the Global Lattice Energy Explorer (GLEE) software, a few of these extensions are briefly discussed.
910–924
Case, David H.
5697af1e-06b6-4e46-83eb-185cec9699ec
Campbell, Josh E.
09d87084-e709-457b-8a97-1b12acdd1b56
Bygrave, Peter J.
5b60f2a0-1477-43f6-a6a4-aa5a2804a549
Day, Graeme M.
e3be79ba-ad12-4461-b735-74d5c4355636
2016
Case, David H.
5697af1e-06b6-4e46-83eb-185cec9699ec
Campbell, Josh E.
09d87084-e709-457b-8a97-1b12acdd1b56
Bygrave, Peter J.
5b60f2a0-1477-43f6-a6a4-aa5a2804a549
Day, Graeme M.
e3be79ba-ad12-4461-b735-74d5c4355636
Case, David H., Campbell, Josh E., Bygrave, Peter J. and Day, Graeme M.
(2016)
Convergence properties of crystal structure prediction by quasi-random sampling.
Journal of Chemical Theory and Computation, .
(doi:10.1021/acs.jctc.5b01112).
Abstract
Generating sets of trial structures that sample the configurational space of crystal packing possibilities is an essential step in the process of an ab initio crystal structure prediction (CSP). One effective methodology for performing such a search relies on low-discrepancy, quasi-random sampling, and our implementation of such a search for molecular crystals is described in this paper. Herein we restrict ourselves to rigid organic molecules, and by considering their geometric properties, build trial crystal packings as starting points for local lattice energy minimization. We also describe a method to match instances of the same structure, which we use to measure the convergence of our packing search towards completeness. The use of these tools is demonstrated for a set of molecules with diverse molecular characteristics and as representative of areas of application where CSP has been applied. An important finding is that the lowest energy crystal structures are typically located early and frequently during a quasi-random search of phase space. It is usually the complete sampling of higher energy structures that requires extended sampling. We show how the procedure can first be refined, through targetting the volume of the generated crystal structures, and then extended across a range of space groups to make a full CSP search and locate experimentally observed and lists of hypothetical polymorphs. As the described method has also been created to lie at the base of more involved approaches to CSP, which are being developed within the Global Lattice Energy Explorer (GLEE) software, a few of these extensions are briefly discussed.
Text
acs.jctc.5b01112
- Version of Record
Text
Struct Gen ACS Just Accepted
- Other
Text
Supporting Information
- Other
Text
Structure Generator JCTC 2016
- Other
More information
Accepted/In Press date: 30 December 2015
e-pub ahead of print date: 30 December 2015
Published date: 2016
Organisations:
Chemistry
Identifiers
Local EPrints ID: 385478
URI: http://eprints.soton.ac.uk/id/eprint/385478
ISSN: 1549-9618
PURE UUID: 99cede2e-c863-49d5-adb1-3a7c511f7d0c
Catalogue record
Date deposited: 20 Jan 2016 10:10
Last modified: 15 Mar 2024 03:44
Export record
Altmetrics
Contributors
Author:
David H. Case
Author:
Josh E. Campbell
Author:
Peter J. Bygrave
Download statistics
Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.
View more statistics