Evidence map›Paper›PMID 30746448›Full record

ArticleScience advances2019

Reliable and practical computational description of molecular crystal polymorphs.

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

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Article in Science advances, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 81 papers.

0numbers the graph read from it
0cells of the map it votes in
81citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

Who cites it

81 citing papers in PubMed.

  1. Article
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  4. Best practices in `0 K' DFT energy calculations on molecular crystal structures.Acta crystallographica. Section C, Structural chemistry · 2026
    Article
  5. Adiabatic Connection Methods Applied to Molecular Crystals.Journal of chemical theory and computation · 2026
    Article
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  8. ConvergingCrystEngComm · 2026
    Article
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  18. Review
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21 more citing papers are in PubMed but not listed here.

4 · The record

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5 · Who and what money

Authors and funding

6 authors.

Johannes HojaPhysics and Materials Science Research Unit, University of Luxembourg, L-1511 Luxembourg, Luxembourg.ORCID 0000-0003-4138-2124
Hsin-Yu KoDepartment of Chemistry, Princeton University, Princeton, NJ 08544, USA.ORCID 0000-0003-1619-6514
Marcus A NeumannAvant-garde Materials Simulation Deutschland GmbH, Alte Str. 2, 79249 Merzhausen, Germany.
Roberto CarDepartment of Chemistry, Princeton University, Princeton, NJ 08544, USA.ORCID 0000-0001-5243-2647
Robert A DiStasioDepartment of Chemistry and Chemical Biology, Cornell University, Ithaca, NY 14853, USA.ORCID 0000-0003-2732-194X
Alexandre TkatchenkoPhysics and Materials Science Research Unit, University of Luxembourg, L-1511 Luxembourg, Luxembourg.ORCID 0000-0002-1012-4854

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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 to within 1 kJ/mol per molecule. 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.

Identifiers

PMID30746448
PMCPMC6357866

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.