Zheng Jonathan W, Green William H
Department of Chemical Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, United States.
J Phys Chem A. 2023 Dec 7;127(48):10268-10281. doi: 10.1021/acs.jpca.3c05514. Epub 2023 Nov 27.
Although charged solutes are common in many chemical systems, traditional solvation models perform poorly in calculating solvation energies of ions. One major obstacle is the scarcity of experimental data for solvated ions. In this study, we release an experiment-based aqueous ionic solvation energy data set, IonSolv-Aq, that contains hydration free energies for 118 anions and 155 cations, more than 2 times larger than the set of hydration free energies for singly charged ions contained in the 2012 Minnesota Solvation Database commonly used in benchmarking studies. We discuss sources of systematic uncertainty in the data set and use the data to examine the accuracy of popular implicit solvation models COSMO-RS and SMD for predicting solvation free energies of singly charged ionic solutes in water. Our results indicate that most SMD and COSMO-RS modeling errors for ionic solutes are systematic and correctable with empirical parameters. We discuss two systematic offsets: one across all ions and one that depends on the functional group of the ionization site. After correcting for these offsets, solvation energies of singly charged ions are predicted using COSMO-RS to 3.1 kcal mol MAE against a challenging test set and 1.7 kcal mol MAE (about 3% relative error) with a filtered test set. The performance of SMD is similar, with MAE against those same test sets of 2.7 and 1.7 kcal mol. These results underscore the importance of compiling larger experimental data sets to improve solvation model parametrization and fairly assess performance.
尽管带电溶质在许多化学体系中很常见,但传统的溶剂化模型在计算离子的溶剂化能时表现不佳。一个主要障碍是缺乏溶剂化离子的实验数据。在本研究中,我们发布了一个基于实验的水性离子溶剂化能数据集IonSolv-Aq,其中包含118种阴离子和155种阳离子的水合自由能,比基准研究中常用的2012年明尼苏达溶剂化数据库中包含的单电荷离子水合自由能数据集大两倍多。我们讨论了数据集中系统不确定性的来源,并使用这些数据来检验流行的隐式溶剂化模型COSMO-RS和SMD预测水中单电荷离子溶质溶剂化自由能的准确性。我们的结果表明,离子溶质的大多数SMD和COSMO-RS建模误差是系统性的,可以通过经验参数进行校正。我们讨论了两个系统偏差:一个是所有离子的偏差,另一个取决于电离位点的官能团。校正这些偏差后,使用COSMO-RS预测单电荷离子的溶剂化能,对于具有挑战性的测试集,平均绝对误差为3.1 kcal/mol,对于经过筛选的测试集,平均绝对误差为1.7 kcal/mol(约3%的相对误差)。SMD的性能类似,与相同测试集的平均绝对误差分别为2.7和1.7 kcal/mol。这些结果强调了汇编更大的实验数据集以改进溶剂化模型参数化并公平评估性能的重要性。