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Accurate and efficient representation of intra­molecular energy in ab initio generation of crystal structures. I. Adaptive local approximate models

The global search stage of crystal structure prediction (CSP) methods requires a fine balance between accuracy and computational cost, particularly for the study of large flexible molecules. A major improvement in the accuracy and cost of the intramolecular energy function used in the CrystalPredict...

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Detalles Bibliográficos
Autores principales: Sugden, Isaac, Adjiman, Claire S., Pantelides, Constantinos C.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: International Union of Crystallography 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5134761/
https://www.ncbi.nlm.nih.gov/pubmed/27910837
http://dx.doi.org/10.1107/S2052520616015122
Descripción
Sumario:The global search stage of crystal structure prediction (CSP) methods requires a fine balance between accuracy and computational cost, particularly for the study of large flexible molecules. A major improvement in the accuracy and cost of the intramolecular energy function used in the CrystalPredictor II [Habgood et al. (2015 ▸). J. Chem. Theory Comput. 11, 1957–1969] program is presented, where the most efficient use of computational effort is ensured via the use of adaptive local approximate model (LAM) placement. The entire search space of the relevant molecule’s conformations is initially evaluated using a coarse, low accuracy grid. Additional LAM points are then placed at appropriate points determined via an automated process, aiming to minimize the computational effort expended in high-energy regions whilst maximizing the accuracy in low-energy regions. As the size, complexity and flexibility of molecules increase, the reduction in computational cost becomes marked. This improvement is illustrated with energy calculations for benzoic acid and the ROY molecule, and a CSP study of molecule (XXVI) from the sixth blind test [Reilly et al. (2016 ▸). Acta Cryst. B72, 439–459], which is challenging due to its size and flexibility. Its known experimental form is successfully predicted as the global minimum. The computational cost of the study is tractable without the need to make unphysical simplifying assumptions.