Quantitative structure-property relationship studies on electrochemical degradation of substituted phenols using a support vector machine

Abstract

A quantitative structure-property relationship (QSPR) model has been developed for the electrochemical degradation of substituted phenols using a support vector machine (SVM). Thirty descriptors, including quantum chemical parameters, steric effect descriptors and half wave potential (E 1/2), were used for describing twelve substituted phenols, including mono- and multi-substituent phenols. A leave-one-out (LOO) cross validation procedure resulted in the selection of three descriptors, the total of electron and nuclear energies of the two-center terms for the carbon–chlorine or carbon–nitrogen bond (TE2), the net atomic charges on the chlorine or nitrogen (q x), and the largest negative atomic charge on an atom (q −). The model based on SVM yielded a Q 2 value of 0.892, indicating a high predictive ability. Compared with models developed with partial least squares (PLS) and multiple linear regression (MLR), where Q 2 were 0.804 and 0.799 respectively, SVM showed higher performances.