Density Functionals for Hydrogen Storage: Defining the H2Bind275 Test Set with Ab Initio Benchmarks and Assessment of 55 Functionals

Efficient and high-capacity storage
materials are indispensable
for a hydrogen-based economy. In silico tools can accelerate the process
of discovery of new adsorbent materials with optimal hydrogen adsorption
enthalpies. Density functional theory is well-poised to become a very
useful tool for enabling high-throughput screening of potential materials.
In this work, we have identified density functional approximations
that provide good performance for hydrogen binding applications following
a two-pronged approach. First, we have compiled a data set (H2Bind275)
that comprehensively represents the hydrogen binding problem capturing
the chemical and mechanistic diversity in the binding sites encountered
in hydrogen storage materials. We have also computed reference interaction
energies for this data set using coupled-cluster theory. Second, we
have assessed the performance of 55 density functional approximations
for predicting H2 interaction energies and have identified
two hybrid density functionals (ωB97X-V and ωB97M-V),
two double hybrid density functionals (DSD-PBEPBE-D3­(BJ) and PBE0-DH),
and one semilocal density functional (B97M-V) as the best performing
ones. We have recommended the addition of empirical dispersion corrections
to systematically underbinding density functionals such as revPBE,
BLYP, and B3LYP for improvements in performance at negligible additional
cost. We have also recommended the usage of the def2-TZVPP basis set
as it represents a good compromise between accuracy and cost, limiting
the finite basis set errors to less than 1 kJ/mol.