Automated high-throughput organic crystal structure prediction <i>via</i> population-based sampling
With advancements in computational molecular modeling and powerful structure search methods, it is now possible to systematically screen crystal structures for small organic molecules.
Authors
- Shinnosuke Hattori (ORCID: https://orcid.org/0000-0003-0786-1308)
- Qiang Zhu (ORCID: https://orcid.org/0000-0002-9892-0344)
Institutions
- University of North Carolina at Charlotte (US)
- Sony (Taiwan) (TW)
Publication Details
- Journal
- Digital Discovery
- Published
- 2024-11-20
- DOI
- https://doi.org/10.1039/d4dd00264d
- Citations
- 5
- Primary Topic
- Machine Learning in Materials Science
- Type
- article
- Field-Weighted Citation Impact
- 0.59
Funders
- National Science Foundation
- Division of Materials Research