An invertible, invariant crystal representation for inverse design of solid-state materials using generative deep learning

The past decade has witnessed rapid progress in deep learning for molecular design, owing to the availability of invertible and invariant representations for molecules such as simplified molecular-input line-entry system (SMILES), which has powered cheminformatics since the late 1980s. However, the...

Descripción completa

Detalles Bibliográficos
Autores principales: Xiao, Hang, Li, Rong, Shi, Xiaoyang, Chen, Yan, Zhu, Liangliang, Chen, Xi, Wang, Lei
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2023
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10622439/
https://www.ncbi.nlm.nih.gov/pubmed/37919277
http://dx.doi.org/10.1038/s41467-023-42870-7

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10622439/
https://www.ncbi.nlm.nih.gov/pubmed/37919277
http://dx.doi.org/10.1038/s41467-023-42870-7

Ejemplares similares