Liu Xiao, Spiekermann Kevin A, Menon Angiras, Green William H, Head-Gordon Martin
Kenneth S. Pitzer Center for Theoretical Chemistry, Department of Chemistry, University of California, Berkeley, California 94720, USA.
Department of Chemical Engineering, Massachusetts Institute of Technology, Cambridge, MA 02139, USA.
Phys Chem Chem Phys. 2025 Jun 25;27(25):13326-13339. doi: 10.1039/d5cp01181g.
Accurate prediction of barrier heights and reaction energies is of paramount importance for reaction kinetics. For computational efficiency, such calculations are typically performed with density functional theory (DFT) methods, with accuracy that depends critically on the choice of functional. The RDB7 dataset (K. A. Spiekermann, L. Pattanaik and W. H. Green, High Accuracy Barrier Heights, Enthalpies, and Rate Coefficients for Chemical Reactions, , 2022, , 417) is a diverse chemical kinetics data set that covers 11 926 reactions and their barriers to assess present-day functionals. Strikingly, the RDB7 barrier heights reported using a reputable rung 4 hybrid functional (ωB97X-D3) exhibited significantly larger errors than seen in other benchmarks. Here, we identify the sources of error, and to the extent possible, address those sources. We categorize the barrier heights and reaction energies into three subsets based on orbital stability analysis. The "easy" subset has orbitals that are stable at the mean-field Hartree-Fock (HF) level, which implies weak correlation effects. An "intermediate" subset exhibits spin symmetry breaking at the HF level, but the restricted orbitals are stable at the dynamically correlated orbital optimized second order Møller-Plesset (-OOMP2) level with = 1.45. While more challenging than the easy category, this implies that correlation effects are still not strong. The remaining "difficult" subset is expected to be significantly affected by strong electron correlations, which potentially affects the accuracy of standard DFT. With this data classification, we performed new benchmarks with unrestricted ωB97X-D3 as well as two other hybrid functionals, ωB97M-V, and MN15, and the double hybrid ωB97M(2) functional. The RMSD values on the easy subset are comparable to prior high-quality benchmark studies, while the performance of all functionals on the intermediate subset is consistently less good. By far the largest errors lie in the difficult subset involving strongly correlated species. We refined some of the previous reference values to further assess the two key error sources: the density functional and its associated orbitals, and the reduced reliability of the previous RHF:RCCSD(T)-F12 reference. We propose our orbital stability classification as a best-practice approach for DFT calculations in chemical kinetics involving even numbers of electrons, as it provides useful information about the expected accuracy. We strongly recommend the routine use of orbital stability analysis in DFT calculations, as the spin-polarized solutions significantly reduce the strong correlation errors seen with spin-restricted orbitals.
准确预测势垒高度和反应能量对于反应动力学至关重要。为了提高计算效率，此类计算通常采用密度泛函理论（DFT）方法，其准确性关键取决于泛函的选择。RDB7数据集（K. A. 斯皮克曼、L. 帕塔纳伊克和W. H. 格林，《化学反应的高精度势垒高度、焓和速率系数》，2022年，第417页）是一个多样化的化学动力学数据集，涵盖11926个反应及其势垒，用于评估当前的泛函。引人注目的是，使用声誉良好的第4级杂化泛函（ωB97X-D3）报告的RDB7势垒高度显示出比其他基准测试中更大的误差。在这里，我们确定误差来源，并尽可能解决这些来源。我们根据轨道稳定性分析将势垒高度和反应能量分为三个子集。“简单”子集的轨道在平均场哈特里-福克（HF）水平上是稳定的，这意味着相关效应较弱。“中等”子集在HF水平上表现出自旋对称性破缺，但受限轨道在动态相关的轨道优化二阶莫勒-普列斯特定理（-OOMP2）水平（ = 1.45）上是稳定的。虽然比简单类别更具挑战性，但这意味着相关效应仍然不强。其余的“困难”子集预计会受到强电子相关性的显著影响，这可能会影响标准DFT的准确性。通过这种数据分类，我们使用无限制的ωB97X-D3以及另外两个杂化泛函ωB97M-V和MN15，以及双杂化ωB97M(2)泛函进行了新的基准测试。简单子集上的均方根偏差（RMSD）值与先前的高质量基准研究相当，而所有泛函在中等子集上的性能始终较差。迄今为止，最大的误差存在于涉及强相关物种的困难子集中。我们改进了一些先前的参考值，以进一步评估两个关键误差来源：密度泛函及其相关轨道，以及先前RHF:RCCSD(T)-F12参考的可靠性降低。我们提出我们的轨道稳定性分类作为涉及偶数电子的化学动力学中DFT计算的最佳实践方法，因为它提供了有关预期准确性的有用信息。我们强烈建议在DFT计算中常规使用轨道稳定性分析，因为自旋极化解显著降低了自旋受限轨道中出现的强相关误差。
