Quantitative structure-property relationship studies on electrochemical degradation of substituted phenols using a support vector machine
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.
electrochemical substituted phenols qspr support vector machine (svm) partial least squares (pls)