Accelerating the prediction of CO(2) capture at low partial pressures in metal-organic frameworks using new machine learning descriptors

Metal-Organic frameworks (MOFs) have been considered for various gas storage and separation applications. Theoretically, there are an infinite number of MOFs that can be created; however, a finite amount of resources are available to evaluate each one. Computational methods can be adapted to expedit...

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Detalles Bibliográficos
Autores principales: Orhan, Ibrahim B., Le, Tu C., Babarao, Ravichandar, Thornton, Aaron W.
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/PMC10547688/
https://www.ncbi.nlm.nih.gov/pubmed/37789142
http://dx.doi.org/10.1038/s42004-023-01009-x

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10547688/
https://www.ncbi.nlm.nih.gov/pubmed/37789142
http://dx.doi.org/10.1038/s42004-023-01009-x

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