To better understand the thermochemical kinetics and
mechanism
of a specific chemical reaction, an accurate estimation of barrier
heights (forward and reverse) and reaction energies is vital. Because
of the large size of reactants and transition state structures involved
in real-life mechanistic studies (e.g., enzymatically catalyzed reactions),
density functional theory remains the workhorse for such calculations.
In this paper, we have assessed the performance of 91 density functionals
for modeling the reaction energies and barrier heights on a large
and chemically diverse data set (BH9) composed of 449 organic chemistry
reactions. We have shown that range-separated hybrid functionals perform
better than the global hybrids for BH9 barrier heights and reaction
energies. Except for the PBE-based range-separated nonempirical double
hybrids, range separation of the exchange term helps improve the performance
for barrier heights and reaction energies. The 16-parameter Berkeley
double hybrid, ωB97M(2), performs remarkably well for both properties.
However, our minimally empirical range-separated double hybrid functionals
offer marginally better accuracy than ωB97M(2) for BH9 barrier
heights and reaction energies.