Author/Authors :
Liu، H نويسنده School of Biological and Chemical Engineering, Jiaxing University, Zhejiang Jiaxing, 314001, People’s Republic of China , , Tan، J نويسنده School of Biological and Chemical Engineering, Jiaxing University, Zhejiang Jiaxing, 314001, People’s Republic of China , , Yu، H X نويسنده State Key Laboratory of Pollution Control and Resources Reuse, School of Environment, Nanjing University, Jiangsu Nanjing 210093, People’s Republic of China , , Liu، H.X نويسنده School of Biological and Chemical Engineering, Jiaxing University, Zhejiang Jiaxing, 314001, People’s Republic of China , , Wang، L S نويسنده State Key Laboratory of Pollution Control and Resources Reuse, School of Environment, Nanjing University, Jiangsu Nanjing 210093, People’s Republic of China , , Wang، Z Y نويسنده School of Biological and Chemical Engineering, Jiaxing University, Zhejiang Jiaxing, 314001, People’s Republic of China ,
Abstract :
Although extensive experimental work has been carried out during the last several years,
experimental reaction rate constants are available only for hundreds of compounds. Therefore, it is useful to
develop a theoretical prediction method, which can be used to obtain estimates of the necessary kinetic
parameters. One of the most successful approaches to predict chemical properties starting only from molecu-
lar structural information is quantitative structure–activity/property relationships modeling (QSAR/QSPR).
The purpose of this paper is to study the relationships between concentrations of 26 substituted phenols and
reaction times during the ozonation process and determine the reaction orders and apparent reaction rate
constants (-lgk´). Then, optimized geometries of the substituted phenols were carried out at the B3LYP/6-
311G** level using the Gaussian 03 software package. The structural and thermodynamic parameters ob-
tained were taken as theoretical descriptors to establish a novel QSPR/QSAR model for -lgk´ of the substi-
tuted phenols, with a regression coefficient R = 0.909 and standard deviation SD = 0.141. Finally, the stability
of the model for -lgk´ predictions was checked by the t-test, showing satisfactory results. Results obtained
reveal the reliability of QSPR/QSAR model for the prediction of ozone degradations rate constant of organic
compounds.
