Journal of Materials Chemistry A · 2019 · 24 citations · 70 references
Natural SciencesChemical EngineeringChemistryComputational ChemistryMachine LearningTheoretical ChemistryAdsorption ProcessesAdsorptive SeparationsHigh-throughput Materials ScreeningCatalyst DiscoveryGrand Canonical Monte CarloMachine Learning ScreeningSilica RemovalSilicate RemovalZeolite AdsorbentsZeolite AdsorptionZeolites
By a two-step computational process, namely Grand Canonical Monte Carlo (GCMC) simulations and machine learning (ML), we screened 50 959 hypothetical pure-silica zeolites and identified 230 preeminent zeolites with excellent adsorption performances.
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Scikit-learn: Machine Learning in Python
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Monte Carlo sampling methods using Markov chains and their applications
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