Systematic Identification of Multimetallic Catalysts for Electrochemical CO2 Reduction Using Quantum Chemical Modeling and Machine Learning

The integration of quantum chemical modeling with machine learning enables a novel approach for accelerating catalyst discovery for challenging target reactions. The molecular-level model bridges the gap between our knowledge about fundamental catalysis mainly derived from single-crystal models and the desire to design multimetallic nanoparticles with desired catalytic propertie.