Optimization of VASPsol Solvation Free Energy Predictions

Density functional theory can accurately predict material properties and reaction barriers. However, it is often limited to small system sizes due to high computational costs. In addition, many properties and reaction barriers are dramatically different when solvated. To approximate the solvation effect, computational chemists use continuum models to mimic the countless number of solvent molecules in these systems. Continuum models attempt to capture the effect of the solvent on solute molecules and surfaces while dramatically reducing the computational cost. VASPsol uses a polarizable continuum model within VASP, a plane-wave DFT code. The present work sought to optimize the VASPsol cavity parameters by minimizing solvation energy errors compared to experimentally measured values. The experimental solvation energies are from the Truhlar Minnesota dataset and encompass over 2500 molecules with 80 unique solvents. To minimize the number of evaluations needed to improve VASPsol performance, we used COSMO-SAC sigma-profile descriptors to represent our molecular dataset. We analyzed the resultant errors across chemical groups to optimize VASPsol parameters for multiple solvents. We show that using these optimized parameters, VASPsol can lead to more accurate simulations for the larger community.