Infrared spectroscopy data- and physics-driven machine learning for characterizing surface microstructure of complex materials

Abstract

Knowing compositional motifs of nanoparticle catalysts in operando conditions is crucial towards understanding their catalytic behavior. Here, the authors develop a physics-driven machine learning approach to predict adsorption sites for a CO molecule over platinum nanoparticles in a multitude of coordination environments.