Sequential design of adsorption simulations in metal–organic frameworks
Krishnendu Mukherjee, Alexander W. Dowling, Yamil J. Colón
Abstract
An active learning protocol is introduced to sequentially build surrogate models for predicting gas adsorption. The method is shown to work for methane and carbon dioxide adsorption in Cu–BTC MOF for isotherms and pressure–temperature phase space.
Topics & Concepts
AdsorptionMethaneMetal-organic frameworkWork (physics)Carbon dioxideMaterials scienceCharacterisation of pore space in soilPhase (matter)Chemical engineeringThermodynamicsChemistryPhysical chemistryOrganic chemistryPhysicsEngineeringComposite materialPorosityMetal-Organic Frameworks: Synthesis and ApplicationsMachine Learning in Materials SciencePhase Equilibria and Thermodynamics