Assessment of the Performance of Density Functionals for Predicting Potential Energy Curves in Hydrogen Storage Applications

Abstract

The availability of accurate computational tools for modeling and simulation is vital to accelerate the discovery of materials capable of storing hydrogen (H 2 ) under given parameters of pressure swing and temperature. Previously, we compiled the H2Bind275 dataset consisting of equilibrium geometries and assessed the performance of 55 density functionals over this dataset (Veccham, S. P.; Head-Gordon, M. J. Chem. Theory Comput., 2020, 16, 4963-4982). As it is crucial for computational tools to accurately model the entire potential energy curve (PEC), in addition to the equilibrium geometry, we have extended this dataset with 389 new data points to include two compressed and three elongated geometries along 78 PECs for H 2 binding, forming the H2Bind78×7 dataset. Assessing the performance of 55 density functionals on this significantly larger and more comprehensive H2Bind78×7 dataset, we have identified the best performing density functionals for H 2 binding applications: PBE0-DH, ωB97X-V, ωB97M-V, and DSD-PBEPBE-D3(BJ). Addition of Hartree Fock exchange improves the performance