System-specific reparameterization of density functionals with machine learning: application to spin-splitting energies of transition metal complexes

Accurate estimates of the spin-splitting energy (SSE) are essential for proper modeling of transition metal complex (TMC) catalysts and functional materials but are notoriously challenging to achieve. Over a large set of over 450 TMCs, we demonstrate that adding Hartree–Fock exchange (HFX) to semilocal density functionals (e.g., PBE or SCAN) in a system-specific fashion provides the flexibility to significantly reduce errors relative to reference wavefunction theory (i.e., DLPNO-CCSD(T))...