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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

机译:溶剂对离子液体与分子溶剂混合物中芳香亲核取代反应动力学的影响及人工神经网络预测

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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°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 artificial neural network model.These improvements are due to the fact that the reaction rate constant shows nonlinear correlations with the solvatochromic parameters.
机译:在25℃下,研究了1-乙基-3-甲基咪唑乙基硫酸盐([EMIM] [EtSO4])与​​甲醇,氯仿和二甲基亚砜的混合物中1-氯-2,4-二硝基苯与苯胺之间反应的动力学。 log k_A与归一化极性参数(E_T〜N),氢键受体碱度β,氢键供体酸度α和介质的双极性/极化率(PI *)的参数相关性未给出可接受的结果。 log k_A与溶剂变色参数的多参数线性回归(MLR)表明,反应速率常数随E_T〜N,pi *和beta的增加而增大,随alpha参数的减小而减小。为准确预测溶剂对速率常数的影响,优化了人工神经网络通过三个输入(包括alpha,pi *和beta参数)对预测集中的log k_A值进行预测,发现正确选择和训练的神经网络可以公平地表示反应速率常数对s的依赖性MLR模型的预测值的平均偏差5.023与人工神经网络模型的0.343的值应进行比较,这些改进归因于以下事实:反应速率常数与溶剂化变色参数显示非线性相关性。

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