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Machine learning enables interpretable discovery of innovative polymers for gas separation membranes

Polymer membranes perform innumerable separations with far-reaching environmental implications. Despite decades of research, design of new membrane materials remains a largely Edisonian process. To address this shortcoming, we demonstrate a generalizable, accurate machine learning (ML) implementatio...

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Detalles Bibliográficos
Autores principales:	Yang, Jason, Tao, Lei, He, Jinlong, McCutcheon, Jeffrey R., Li, Ying
Formato:	Online Artículo Texto
Lenguaje:	English
Publicado:	American Association for the Advancement of Science 2022
Materias:	Physical and Materials Sciences
Acceso en línea:	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9299556/ https://www.ncbi.nlm.nih.gov/pubmed/35857839 http://dx.doi.org/10.1126/sciadv.abn9545

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