Preview of machine learning the quantum-chemical properties of metal–organic frameworks for accelerated materials discovery

Metal–organic frameworks (MOFs) are a class of chemical compounds used for the storage of gases such as hydrogen and carbon dioxide. They also have potential applications in gas purification, catalysis and as supercapacitors. A database of quantum-chemical properties for over 14,000 MOF structures (...

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Detalles Bibliográficos
Autor principal: Callaghan, Sarah
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2021
Materias:
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Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8085598/
https://www.ncbi.nlm.nih.gov/pubmed/33982029
http://dx.doi.org/10.1016/j.patter.2021.100239
Descripción
Sumario:Metal–organic frameworks (MOFs) are a class of chemical compounds used for the storage of gases such as hydrogen and carbon dioxide. They also have potential applications in gas purification, catalysis and as supercapacitors. A database of quantum-chemical properties for over 14,000 MOF structures (the “QMOF database”) has been created and made available to the community along with code for machine learning and other related resources.

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