Machine learning unifies the modeling of materials and molecules

Determining the stability of molecules and condensed phases is the cornerstone of atomistic modeling, underpinning our understanding of chemical and materials properties and transformations. We show that a machine-learning model, based on a local description of chemical environments and Bayesian sta...

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Detalles Bibliográficos
Autores principales: Bartók, Albert P., De, Sandip, Poelking, Carl, Bernstein, Noam, Kermode, James R., Csányi, Gábor, Ceriotti, Michele
Formato: Online Artículo Texto
Lenguaje:English
Publicado: American Association for the Advancement of Science 2017
Materias:
Research Articles
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5729016/
https://www.ncbi.nlm.nih.gov/pubmed/29242828
http://dx.doi.org/10.1126/sciadv.1701816

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5729016/
https://www.ncbi.nlm.nih.gov/pubmed/29242828
http://dx.doi.org/10.1126/sciadv.1701816

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