Diffusion coefficient (D) is important to evaluate the performance of passive samplers and to monitor the concentration of chemicals effectively. Herein, we developed a polyparameter linear free energy relationship (pp-LFER) model and a quantitative structure-property relationship (QSPR) model for the prediction of diffusion coefficients of hydrophobic organic contaminants (HOCs) in low density polyethylene (LDPE). A dataset of 120 various chemicals was used to develop both models. The pp-LFER model was developed with two descriptors (V and E) and the statistical parameters of the model showed satisfactory results. As a further exploration of the diffusion behavior of the compounds, a QSPR model with five descriptors (ETA_Alpha, ASP-6, IC1, TDB6r and ATSC2v) was constructed with adjusted determination coefficient (R2) of 0.949 and cross-validation coefficient (QLoo2) of 0.941. The regression results indicated that both models had satisfactory goodness-of-fit and robustness. This study proves that pp-LFER and QSPR approaches are available for the prediction of log D values for the hydrophobic organic compounds within the applicability domain.

中文翻译：

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建立用于预测LDPE中疏水性有机化合物扩散系数的pp-LFER和QSPR模型。

扩散系数（D）对于评估被动采样器的性能并有效监控化学物质浓度非常重要。本文中，我们开发了用于预测低密度聚乙烯（LDPE）中疏水性有机污染物（HOCs）扩散系数的多参数线性自由能关系（pp-LFER）模型和定量结构-性质关系（QSPR）模型。使用120种各种化学物质的数据集来开发两个模型。用两个描述符（V和E）开发了pp-LFER模型，该模型的统计参数显示出令人满意的结果。为了进一步探索化合物的扩散行为，构建了具有五个描述符（ETA_Alpha，ASP-6，IC1，TDB6r和ATSC2v）的QSPR模型，调整后的测定系数（R2）为0。949，交叉验证系数（QLoo2）为0.941。回归结果表明，两个模型均具有令人满意的拟合优度和鲁棒性。这项研究证明pp-LFER和QSPR方法可用于预测适用范围内的疏水性有机化合物的log D值。