摘要polychlorinated dibenzothiophenes (PCDTs) are a groun of impoutant persistent organic properties In the present study,geometrical optimization and electrostatic potential calculations have been performed for all 135 PCDTs congeners at the B3LYP/6-31G* level of theory. By means of the VSMP (variable selection and modeling based on prediction) program, one optimal descriptor (molecular polarizability, α) was selected to develop a QSRR model for the prediction of gas chromatographic retention indices (GC-RI) of PCDTs. The estimated correlation coefficients (r2) and LOO-validated correlation coefficients (q2), all more than 0.99, were built by multiple linear regression, which shows a good estimation ability and stability of the models. A prediction power for the external samples was validated by the model built from the training set with 17 polychlorinated dibenzothiophenes.
Polychlorinated dibenzothiophenes (PCDTs) are a group of important persistent organic pollutants. In the present study, geometrical optimization and electrostatic potential calculations have been performed for all 135 PCDTs congeners at the B3LYP/6-31G* level of theory. By means of the VSMP (variable selection and modeling based on prediction) program, one optimal descriptor (molecular polarizability, α) was selected to develop a QSRR model for the prediction of gas chromatographic retention indices (GC-RI) of PCDTs. The estimated correlation coefficients (r2) and LOO-validated correlation coefficients (q2), all more than 0.99, were built by multiple linear regression, which shows a good estimation ability and stability of the models. A prediction power for the external samples was validated by the model built from the training set with 17 polychlorinated dibenzothiophenes.
刘红艳;莫凌云;李艳红;易忠胜. Prediction of Gas Chromatographic Retention Indices of Organophosphates by DFT and VSMP Method[J]. , 2012, 31(5): 704-712.
LIU Hong-Yan;MO Ling-Yun;LI Yan-Hong;YI Zhong-Sheng. Prediction of Gas Chromatographic Retention Indices of Organophosphates by DFT and VSMP Method. , 2012, 31(5): 704-712.
2012, Vol. 31 
