College of Chemistry, Sichuan University, Chengdu 610065, People's Republic of China.
J Comput Chem. 2010 Nov 15;31(14):2585-92. doi: 10.1002/jcc.21550.
This article describes a multiparameter calibration model, which improves the accuracy of density functional theory (DFT) for the prediction of standard enthalpies of formation for a large set of organic compounds. The model applies atom based, bond based, electronic, and radical environmental correction terms to calibrate the calculated enthalpies of formation at B3LYP/6-31G(d,p) level by a least-square method. A diverse data set of 771 closed-shell compounds and radicals is used to train the model. The leave-one-out cross validation squared correlation coefficient q(2) of 0.84 and squared correlation coefficient r(2) of 0.86 for the final model are obtained. The mean absolute error in enthalpies of formation for the dataset is reduced from 4.9 kcal/mol before calibration to 2.1 kcal/mol after calibration. Five-fold cross validation is also used to estimate the performance of the calibration model and similar results are obtained.
本文描述了一种多参数校准模型,该模型提高了密度泛函理论(DFT)对大量有机化合物标准生成焓预测的准确性。该模型通过最小二乘法应用基于原子、基于键、基于电子和基于自由基环境的校正项,对 B3LYP/6-31G(d,p)水平计算的生成焓进行校准。使用了 771 种闭壳化合物和自由基的多样化数据集来训练模型。最终模型的留一交叉验证平方相关系数 q(2)为 0.84,平方相关系数 r(2)为 0.86。数据集的生成焓平均绝对误差从校准前的 4.9 kcal/mol 降低到校准后的 2.1 kcal/mol。还使用五倍交叉验证来估计校准模型的性能,得到了类似的结果。