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

Sarah Callaghan

2021Patterns32 citationsDOIOpen Access PDF

Abstract

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.

Topics & Concepts

Metal-organic frameworkSupercapacitorMaterials scienceHydrogenHydrogen storageCarbon fibersNanotechnologyChemistryOrganic chemistryAdsorptionElectrodeComposite numberElectrochemistryPhysical chemistryComposite materialMetal-Organic Frameworks: Synthesis and ApplicationsMachine Learning in Materials ScienceX-ray Diffraction in Crystallography
Preview of machine learning the quantum-chemical properties of metal–organic frameworks for accelerated materials discovery | Litcius