A four-descriptor quantitative structure–property relationship model was constructed to predict 65 intrinsic viscosities [η] of polymer solutions. Four quantum chemical descriptors, the traceless quadrupole moment θ_(R), the hydrogen bond or electrostatic attraction descriptor Q_H, the partition function Q_BOT(R) and the frontier orbital descriptor E_HOMO, were calculated with density functional theory at the B3LYP/6-31G(d) level and used to develop the model by multivariate linear regression (MLR) analysis. The model possesses coefficients of determination r² of 0.827 for the training set and 0.808 for the test set, and shows better statistical characteristics than the existing MLR models of intrinsic viscosities [η] of polymer–solvent combinations. Moreover, the four descriptors were used to develop a support vector machine model for [η] that possesses a coefficient of determination r² of 0.911 for the whole data set.

构建了一个四描述的定量结构-性质关系模型，以预测聚合物溶液的65个固有粘度[ η ]。利用密度泛函理论在B3LYP /处计算了四个量子化学描述符，无痕四极矩θ _（R），氢键或静电吸引描述符Q _H，分配函数Q _BOT（R）和边界轨道描述符E _HOMO。 6-31G（d）级别，用于通过多元线性回归（MLR）分析开发模型。该模型具有确定系数r ²训练集为0.827，测试集为0.808，与现有的聚合物-溶剂组合的固有粘度[ η ] MLR模型相比，具有更好的统计特性。此外，使用四个描述符为[ η ]开发了一个支持向量机模型，对于整个数据集，该模型的确定系数r ²为0.911。