Reliable and practical computational description of molecular crystal polymorphs

Johannes Hoja, Hsin Yu Ko, Marcus A. Neumann, Roberto Car, Robert A. DiStasio, Alexandre Tkatchenko

Research output: Contribution to journalArticlepeer-review

47 Scopus citations

Abstract

Reliable prediction of the polymorphic energy landscape of a molecular crystal would yield profound insight into drug development in terms of the existence and likelihood of late-appearing polymorphs. However, the computational prediction of molecular crystal polymorphs is highly challenging due to the high dimensionality of conformational and crystallographic space accompanied by the need for relative free energies towithin 1 kJ/mol permolecule. In this study, we combine the most successful crystal structure sampling strategy with the most successful first-principles energy ranking strategy of the latest blind test of organic crystal structure prediction methods. Specifically,we present a hierarchical energy ranking approach intended for the refinement of relative stabilities in the final stage of a crystal structure prediction procedure. Such a combined approach provides excellent stability rankings for all studied systems and can be applied to molecular crystals of pharmaceutical importance.

Original languageEnglish (US)
Article numbereaau3338
JournalActa Horticulturae Sinica
Volume45
Issue number12
DOIs
StatePublished - 2019

All Science Journal Classification (ASJC) codes

  • Horticulture
  • General
  • Plant Science

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