Accurate Density Functional Theory for Non-Covalent Interactions in Charged Systems

Accurately modeling non-covalent interactions (NCIs) involving charged systems remains an outstanding challenge in Density Functional Theory (DFT), with implications across natural and life sciences, engineering, e.g., in biochemistry, catalysis, and materials science. For these interactions, the interplay between electrostatics, polarization, and dispersion leads to systematic errors of up to tens of kcal/mol in standard dispersion-enhanced DFT methods. We solve this problem by introducing (r2SCAN+MBD)@HF, a DFT method without empirically fitted parameters that combines the r2SCAN functional and many-body dispersion, both evaluated on Hartree-Fock densities. We show that the unique synergy of these three components enables balanced treatment of short- and long-range correlation, which is crucial for accurate description of NCIs involving charged systems. Evaluations on standard benchmarks and a new Metal Ion Protein Clusters dataset introduced here show that (r2SCAN+MBD)@HF significantly improves accuracy for NCIs involving charged systems while maintaining robust performance for neutral systems. Given the ubiquity of such interactions, (r2SCAN+MBD)@HF is broadly applicable from biochemistry and materials science, including for generating high-quality data to train machine-learning force fields.