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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

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