Quantitative structure-activity relationship models for predicting apparent rate constants of organic compounds with...

Ferrate (VI) (Fe (VI)) is a promising, environmentally friendly multifunctional oxidant widely applied in organic compound degradation. Oxidative kinetics of the apparent second-order rate constants (k_app) of Fe (VI) with organic compounds are critical for modeling oxidation processes. Herein, a quantitative structure-activity relationship (QSAR) model was developed using particle swarm optimization and an extreme learning machine to better understand the laws of the k_app values of organic compounds, including 33 aliphatic and aromatic hydrocarbon derivatives, during degradation by Fe (VI). Seven components-electronic hardness (H), electronic softness (S), ratio of oxygen to carbon atoms (O_n/C_n), energy of the highest occupied molecular orbital (E_HOMO), vertical ionization potential (VIP), maximum nucleophilic reaction index (f(+)_x), and minimum relative electrophilicity index (RE_n) constitute the critical molecular parameters. The developed QSAR model was verified on the basis of the coefficient of determination (R²) and the root mean square error (RMSE): for the training set, R² = 0.924 and RMSE = 1.186, whereas for the test set, R² = 0.996, and RMSE = 0.352. The applicability, reliability, and predictability of the model were verified by estimating the applicability domain (AD) of the model. Furthermore, QSAR models constructed using different methods were compared, and the main impact descriptors and conclusions obtained from previous studies were theoretically analyzed. Results indicate that constructing the QSAR model facilitates k_app prediction for Fe (VI) in the degradation of various organic compounds, improves the understanding of the degradation mechanism, and reduces the pressure on human and material resources caused by experiments.