Universal fragment descriptors for predicting properties of inorganic crystals

Although historically materials discovery has been driven by a laborious trial-and-error process, knowledge-driven materials design can now be enabled by the rational combination of Machine Learning methods and materials databases. Here, data from the AFLOW repository for ab initio calculations is c...

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Detalles Bibliográficos
Autores principales: Isayev, Olexandr, Oses, Corey, Toher, Cormac, Gossett, Eric, Curtarolo, Stefano, Tropsha, Alexander
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group 2017
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5465371/
https://www.ncbi.nlm.nih.gov/pubmed/28580961
http://dx.doi.org/10.1038/ncomms15679

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5465371/
https://www.ncbi.nlm.nih.gov/pubmed/28580961
http://dx.doi.org/10.1038/ncomms15679

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