Materials Science in the AI age: high-throughput library generation, machine learning and a pathway from correlations to the underpinning physics

The use of advanced data analytics and applications of statistical and machine learning approaches (‘AI’) to materials science is experiencing explosive growth recently. In this prospective, we review recent work focusing on generation and application of libraries from both experiment and theoretica...

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Detalles Bibliográficos
Publicado en:MRS Commun
Autores principales: Vasudevan, Rama K., Choudhary, Kamal, Mehta, Apurva, Smith, Ryan, Kusne, Gilad, Tavazza, Francesca, Vlcek, Lukas, Ziatdinov, Maxim, Kalinin, Sergei V., Hattrick-Simpers, Jason
Formato: Artigo
Lenguaje:Inglês
Publicado: 2019
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Article
Acceso en línea:https://ncbi.nlm.nih.gov/pmc/articles/PMC7067066/
https://ncbi.nlm.nih.gov/pubmed/32166045
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1557/mrc.2019.95
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