Benefits of Range-separated Hybrid and Double-Hybrid Functionals for a Large and Diverse Dataset of Reaction Energies and Barrier Heights

TL;DR

This study evaluates 88 density functionals on a large dataset of 449 reactions, finding that range-separated hybrids and double hybrids generally outperform global hybrids in predicting reaction energies and barrier heights.

Contribution

The paper systematically compares the performance of various density functionals, highlighting the superior accuracy of range-separated hybrid and double hybrid functionals for diverse reaction datasets.

Findings

Range-separated hybrids outperform global hybrids for barrier heights and reaction energies.

The {}B97M(2) double hybrid performs exceptionally well.

Range-separated double hybrids offer marginally better accuracy than {}B97M(2).

Abstract

To better understand the thermochemical kinetics and mechanism of a specific chemical reaction, an accurate estimation of barrier heights (forward and reverse) and reaction energy are vital. Due to the large size of reactants and transition state structures involved in real-life mechanistic studies (e.g., enzymatically catalyzed reactions), DFT remains the workhorse for such calculations. In this paper, we have assessed the performance of 88 density functionals for modeling the reaction energies and barrier heights on a large and chemically diverse dataset (BH9) composed of 449 organic chemistry reactions. We have shown that range-separated hybrid functionals perform better than the global hybris for BH9 barrier heights and reaction energies. Except for the PBE-based range-separated nonempirical double hybrids, the exchange term's range separation helps improve the performance for barrier heights and reaction energies. The sixteen-parameter Berkeley double hybrid, {\omega}B97M(2), performs remarkably well for both properties. However, our minimally empirical range-separated double hybrid functionals offer marginally better accuracy than {\omega}B97M(2) for BH9 barrier heights and reaction energies.