Chen, Shuxin

Machine learning to tame divergent density functional approximations: a new path to consensus materials design principles

Machine learning (ML)-based feature analysis reveals universal design rules regardless of density functional choices. Using the consensus among multiple functionals, we identify robust lead complexes in ML-accelerated chemical discovery.