Solvent Effects on Kinetics of an Aromatic Nucleophilic Substitution Reaction in Mixtures of an Ionic Liquid with Molecular Solvents and Prediction Using Artificial Neural Networks

Kinetics of the reaction between 1-chloro-2,4-dinitrobenzene and aniline was studied in mixtures of 1-ethyl-3-methylimidazolium ethylsulfate ([EMIM][EtSO4]) with methanol, chloroform, and dimethylsulfoxide at 25 degrees C. Single-parameter correlations of log k(A) versus normalized polarity parameter (E-T(N)), hydrogen-bond acceptor basicity (beta), hydrogen-bond donor acidity (alpha), and dipolarity/polarizability (pi*) of media do not give acceptable results. Multiparameter linear regression (MLR) of log k(A) versus the solvatochromic parameters demonstrates that the reaction rate constant increases with E-T(N), pi*, and beta and decreases with alpha parameter. To predict accurately solvent effects on the rate constant, optimized artificial neural network with three inputs (including alpha, pi*, and beta parameters) was applied for prediction of the log k(A) values in the prediction set. It was found that properly selected and trained neural network could fairly represent the dependence of the reaction rate constant on solvatochromic parameters. Mean percent deviation of 5.023 for the prediction set by the MLR model should be compared with the value of 0.343 by the artihcial neural network model. These improvements are due to the fact that the reaction rate constant shows nonlinear correlations with the solvatochromic parameters. (C) 2008 Wiley Periodicals, Inc. Int J Chem Kinet 41: 153-159, 2009