Machine learning for design principles for single atom catalysts towards electrochemical reactions
Mohsen Tamtaji, Hanyu Gao, Md Delowar Hossain, Patrick Ryan Galligan, Hoilun Wong, Zhenjing Liu, Hongwei Liu, Yuting Cai, William A. Goddard, Zhengtang Luo
Abstract
Machine learning (ML) integrated density functional theory (DFT) calculations have recently been used to accelerate the design and discovery of heterogeneous catalysts such as single atom catalysts (SACs) through the establishment of deep structure–activity relationships.
Topics & Concepts
Density functional theoryCatalysisAtom (system on chip)ElectrochemistryMaterials scienceNanotechnologyComputer scienceChemistryComputational chemistryPhysical chemistryEmbedded systemOrganic chemistryElectrodeMachine Learning in Materials ScienceElectrocatalysts for Energy ConversionFuel Cells and Related Materials