Inverse design of metal–organic frameworks for direct air capture of CO <sub>2</sub> <i>via</i> deep reinforcement learning
Hyunsoo Park, Sauradeep Majumdar, Xiaoqi Zhang, Jihan Kim, Berend Smit
Abstract
A reinforcement learning framework enables the design and discovery of novel metal–organic frameworks (MOFs) for direct air capture of CO 2 (DAC) in terms of CO 2 heat of adsorption and CO 2 /H 2 O selectivity.
Topics & Concepts
ReinforcementInverseMetal-organic frameworkReinforcement learningEnvironmental scienceArtificial intelligenceComputer scienceMaterials scienceChemistryMathematicsComposite materialPhysical chemistryAdsorptionGeometryMetal-Organic Frameworks: Synthesis and ApplicationsCovalent Organic Framework ApplicationsCarbon Dioxide Capture Technologies