Quantitative structure–property relationships for predicting subcooled liquid vapor pressure (P_L) of 209 polychlorinated diphenyl ethers (PCDEs) by DFT and the position of Cl substitution (PCS) methods

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• 作者：Xiaolan Zeng ; Zunyao Wang ; Zhigang Ge ; Hongxia Liu
• 关键词：Polychlorinated diphenyl ethers (PCDEs) ; Subcooled liquid vapor pressure (P_L) ; Quantitative structure– ; property relationship (QSPR) ; Density functional theory (DFT) ; Position of Cl substitution (PCS) method
• 刊名：Atmospheric Environment
• 出版年：2007
• 出版时间：June 2007
• 年：2007
• 卷：41
• 期：17
• 页码：3590-3603
• 全文大小：221 K

文摘

Optimization of the molecular geometry of 209 polychlorinated diphenyl ethers (PCDEs) and diphenyl ether (DE) were carried out at the B3LYP/6-31G* level with Gaussian 98 program. Based on the theoretical linear solvation energy relationship (TLSER) model, the obtained structural parameters were taken as theoretical descriptors to establish the first novel QSPR model (I) for predicting subcooled liquid vapor pressure (P_L) of PCDEs. The model (I) achieved in this work contains three variables: most negative atomic partial charge in molecule (q⁻), dipole moment of the molecules (μ) and mean molecular polarizability (α), of which r²=0.988, SD=0.134. Meanwhile, it was found that there was significant correlation between the Cl substitution positions and some structural parameters. Consequently, the numbers of Cl substitution positions were also taken as theoretical descriptors to establish the second novel QSPR model (II) for predicting P_L of all PCDE congeners, of which r²=0.991, SD=0.112. In addition, the t-values of two models are both large and the variation inflation factors (VIF) of variables herein are all less than 5.0, suggesting significant statistics of the P_L predicting models. And the results of cross-validation test also showed that the second model exhibited optimum stability and better predictive power. Moreover, results of prediction were further compared with data from similar studies by semi-empirical PM3 method, molecular connectivity indices (MCIs) method and molecular descriptors method.