Acid dissociation constants () are widely measured and studied, most typically in water. Comparatively few datasets and models for non‐aqueous values exist. In this work, we demonstrate how the in one solvent can be accurately determined using reference data in another solvent, corrected by solvation energy calculations from the COSMO‐RS method. We benchmark this approach in 10 different solvents, and find that values calculated in six solvents deviate from experimental data on average by less than 1 unit. We observe comparable performance on a more diverse test set including amino acids and drug molecules, with higher error for large molecules. The model performance in four other solvents is worse, with one MAE exceeding 3 units; we discuss how such errors arise due to both model error and inconsistency in obtaining experimental data. Finally, we demonstrate how this technique can be used to estimate the proton transfer energy between different solvents, and use this to report a value of the proton's solvation energy in formamide, a quantity that does not have a consensus value in literature.

中文翻译：

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非水溶剂中的 pKa 预测


酸解离常数 （） 被广泛测量和研究，最典型的是在水中。存在非水值的数据集和模型相对较少。在这项工作中，我们展示了如何使用另一种溶剂中的参考数据准确确定一种溶剂中的含量，并通过 COSMO-RS 方法的溶剂化能量计算进行校正。我们在 10 种不同的溶剂中对这种方法进行了基准测试，发现在 6 种溶剂中计算的值与实验数据平均偏差不到 1 个单位。我们在包括氨基酸和药物分子在内的更多样化的测试集上观察到类似的性能，而大分子的误差更高。在其他四种溶剂中的模型性能较差，一种 MAE 超过 3 个单位;我们讨论了由于模型误差和获取实验数据的不一致而导致此类误差的产生。最后，我们演示了如何使用该技术来估计不同溶剂之间的质子转移能，并使用它来报告质子在甲酰胺中的溶剂化能值，这个量在文献中没有共识值。