QSAR models for oxidative degradation of organic pollutants in the Fenton process

Abstract

Fenton oxidation is an advanced treatment process used to remove organic pollutants in wastewater. In this study, quantitative structure activity relationship (QSAR) models for Fenton process were developed with reaction rate constants of organic compounds as the dependent variable. To establish optimum QSAR models, reaction rate constants of 33 kinds of organic substances were determined and 13 molecular descriptors were selected. The molecular descriptors were calculated by Hyperchem, Gaussian 09 and Dmol3 software for each organic compound. The optimum QSAR model for predicting the rate constants consists of three descriptors, SAG, f(0)n and EGAP. Among them, SAG appears most critical in determining rate constants. A set of 26 compounds was used as training set to develop models and 7 compounds was used as test set for external validation. The prediction accuracy of the recommended model was tested using the leave-one-out cross validation procedure, validation through an external test set and the Y-randomization evaluation technique. The domain of applicability was finally determined to identify the reliable predictions. The results indicated that the proposed model proved to have significant predictive potential of reaction rate constants in Fenton process.