Direct prediction of gas adsorption via spatial atom interaction learning

Physisorption relying on crystalline porous materials offers prospective avenues for sustainable separation processes, greenhouse gas capture, and energy storage. However, the lack of end-to-end deep learning model for adsorption prediction confines the rapid and precise screen of crystalline porous...

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Detalles Bibliográficos
Autores principales: Cui, Jiyu, Wu, Fang, Zhang, Wen, Yang, Lifeng, Hu, Jianbo, Fang, Yin, Ye, Peng, Zhang, Qiang, Suo, Xian, Mo, Yiming, Cui, Xili, Chen, Huajun, Xing, Huabin
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/PMC10624870/
https://www.ncbi.nlm.nih.gov/pubmed/37923711
http://dx.doi.org/10.1038/s41467-023-42863-6

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10624870/
https://www.ncbi.nlm.nih.gov/pubmed/37923711
http://dx.doi.org/10.1038/s41467-023-42863-6

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