Data-driven design of dual-metal-site catalysts for the electrochemical carbon dioxide reduction reaction
Haisong Feng, Hu Ding, Peinan He, Si Wang, Zeyang Li, Zikang Zheng, Yusen Yang, Min Wei, Xin Zhang
Abstract
A data-driven strategy with a DFT/ML algorithm was reported to predict the catalytic performance of dual-metal-site catalysts (DMSCs) toward CO 2 RR. The screening model successfully predicted 4 DMSCs identified as efficient CO 2 RR electrocatalysts.
Topics & Concepts
CatalysisDual (grammatical number)ElectrochemistryCarbon dioxideReduction (mathematics)MetalElectrochemical reduction of carbon dioxideMaterials scienceInorganic chemistryChemistryPhysical chemistryElectrodeMetallurgyOrganic chemistryMathematicsGeometryCarbon monoxideLiteratureArtCO2 Reduction Techniques and CatalystsMachine Learning in Materials ScienceCatalytic Processes in Materials Science