Department of Materials Science and Engineering, University of California, Berkeley, California 94720, United States.
Materials Science Division, Lawrence Berkeley National Laboratory, Berkeley, California 94720, United States.
J Chem Theory Comput. 2023 Jun 13;19(11):3159-3171. doi: 10.1021/acs.jctc.3c00176. Epub 2023 May 17.
Hydrolysis reactions are ubiquitous in biological, environmental, and industrial chemistry. Density functional theory (DFT) is commonly employed to study the kinetics and reaction mechanisms of hydrolysis processes. Here, we present a new data set, Barrier Heights for HydrOlysis - 36 (BH2O-36), to enable the design of density functional approximations (DFAs) and the rational selection of DFAs for applications in aqueous chemistry. BH2O-36 consists of 36 diverse organic and inorganic forward and reverse hydrolysis reactions with reference energy barriers Δ calculated at the CCSD(T)/CBS level. Using BH2O-36, we evaluate 63 DFAs. In terms of mean absolute error (MAE) and mean relative absolute error (MRAE), ωB97M-V is the best-performing DFA tested, while MN12-L-D3(BJ) is the best-performing pure (nonhybrid) DFA. Broadly, we find that range-separated hybrid DFAs are necessary to approach chemical accuracy (0.043 eV). Although the best-performing DFAs include a dispersion correction to account for long-range interactions, we find that dispersion corrections do not generally improve MAE or MRAE for this data set.
水解反应在生物、环境和工业化学中普遍存在。密度泛函理论（DFT）常用于研究水解过程的动力学和反应机制。在这里，我们提出了一个新的数据集 Barrier Heights for HydrOlysis - 36（BH2O-36），以能够设计密度泛函近似（DFA）并合理选择用于水溶液化学应用的 DFA。BH2O-36 由 36 种不同的有机和无机正向和反向水解反应组成，参考能垒 Δ 在 CCSD(T)/CBS 水平上计算。使用 BH2O-36，我们评估了 63 种 DFA。在平均绝对误差（MAE）和平均相对绝对误差（MRAE）方面，ωB97M-V 是测试性能最佳的 DFA，而 MN12-L-D3(BJ) 是表现最佳的纯（非杂化）DFA。总的来说，我们发现需要使用具有分离范围的杂化 DFA 才能达到化学精度（0.043 eV）。尽管表现最佳的 DFA 包括用于考虑长程相互作用的色散校正，但我们发现对于该数据集，色散校正通常不会提高 MAE 或 MRAE。
