Machine-learned and codified synthesis parameters of oxide materials

Predictive materials design has rapidly accelerated in recent years with the advent of large-scale resources, such as materials structure and property databases generated by ab initio computations. In the absence of analogous ab initio frameworks for materials synthesis, high-throughput and machine...

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Detalles Bibliográficos
Autores principales: Kim, Edward, Huang, Kevin, Tomala, Alex, Matthews, Sara, Strubell, Emma, Saunders, Adam, McCallum, Andrew, Olivetti, Elsa
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group 2017
Materias:
Data Descriptor
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5595045/
https://www.ncbi.nlm.nih.gov/pubmed/28895943
http://dx.doi.org/10.1038/sdata.2017.127

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5595045/
https://www.ncbi.nlm.nih.gov/pubmed/28895943
http://dx.doi.org/10.1038/sdata.2017.127

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