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Interpretable machine learning for accelerating the discovery of metal-organic frameworks for ethane/ethylene separation

Zihao Wang, Teng Zhou, Kai Sundmacher

2022Chemical Engineering Journal75 citationsDOI

Topics & Concepts

PubChemFingerprint (computing)EthyleneMetal-organic frameworkComputer scienceCheminformaticsMolecular descriptorArtificial intelligenceMatching (statistics)SubstructureBiological systemMachine learningBiochemical engineeringChemistryQuantitative structure–activity relationshipEngineeringMathematicsComputational chemistryOrganic chemistryStructural engineeringCatalysisBiologyStatisticsAdsorptionMetal-Organic Frameworks: Synthesis and ApplicationsMachine Learning in Materials ScienceX-ray Diffraction in Crystallography
Interpretable machine learning for accelerating the discovery of metal-organic frameworks for ethane/ethylene separation | Litcius