<scp>MCML</scp> : Combining physical constraints with experimental data for a multi‐purpose meta‐generalized gradient approximation

The predictive power of density functional theory for materials properties can be improved without increasing the overall computational complexity by extending generalized gradient approximation (GGA) electronic exchange and correlation to functionals depending on kinetic energy in addition charge its gradient, resulting a meta-GGA. Here, we propose an empirical meta-GGA model that is based both physical constraints experimental quantum chemistry reference data. optimized MCML yields surface gas phase reaction energetics sacrificing accuracy bulk property predictions existing approaches.