Inverse design with deep generative models: next step in materials discovery

Data-driven inverse design for inorganic functional materials is a rapidly emerging field, which aims to automatically design innovative materials with target properties and to enable property-to-structure material discovery.

Detalles Bibliográficos
Autores principales: Lu, Shuaihua, Zhou, Qionghua, Chen, Xinyu, Song, Zhilong, Wang, Jinlan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2022
Materias:
Perspective
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9385454/
https://www.ncbi.nlm.nih.gov/pubmed/35992238
http://dx.doi.org/10.1093/nsr/nwac111

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9385454/
https://www.ncbi.nlm.nih.gov/pubmed/35992238
http://dx.doi.org/10.1093/nsr/nwac111

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