Insightful classification of crystal structures using deep learning

Computational methods that automatically extract knowledge from data are critical for enabling data-driven materials science. A reliable identification of lattice symmetry is a crucial first step for materials characterization and analytics. Current methods require a user-specified threshold, and ar...

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Detalles Bibliográficos
Autores principales: Ziletti, Angelo, Kumar, Devinder, Scheffler, Matthias, Ghiringhelli, Luca M.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2018
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6050314/
https://www.ncbi.nlm.nih.gov/pubmed/30018362
http://dx.doi.org/10.1038/s41467-018-05169-6

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6050314/
https://www.ncbi.nlm.nih.gov/pubmed/30018362
http://dx.doi.org/10.1038/s41467-018-05169-6

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