Polímeros: Ciência e Tecnologia
https://revistapolimeros.org.br/article/doi/10.4322/polimeros.2013.089
Polímeros: Ciência e Tecnologia
Scientific & Technical Article

Prediction of Monomer Reactivity in Radical Copolymerizations from Transition State Quantum Chemical Descriptors

Tan, Zhengde; Deng, Jiyong; Zhang, Shihua; Yu, Xinliang

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Abstract

Abstract: In comparison with the Q-e scheme, the Revised Patterns Scheme: the U, V Version (the U-V scheme) has greatly improved both its accessibility and its accuracy in interpreting and predicting the reactivity of a monomer in free-radical copolymerizations. Quantitative structure-activity relationship (QSAR) models were developed to predict the reactivity parameters u and v of the U-V scheme, by applying genetic algorithm (GA) and support vector machine (SVM) techniques. Quantum chemical descriptors used for QSAR models were calculated from transition state species with structures C1H3–C2HR3• or •C1H2–C2H2R3 (formed from vinyl monomers C1H2=C2HR3 + H•), using density functional theory (DFT), at the UB3LYP level of theory with 6-31G(d) basis set. The optimum support vector regression (SVR) model of the reactivity parameter u based on Gaussian radial basis function (RBF) kernel (C = 10, ε = 10-5 and γ = 1.0) produced root-mean-square (rms) errors for the training, validation and prediction sets being 0.220, 0.326 and 0.345, respectively. The optimal SVR model for v with the RBF kernel (C = 20, ε = 10-4 and γ = 1.2) produced rms errors for the training set of 0.123, the validation set of 0.206 and the prediction set of 0.238. The feasibility of applying the transition state quantum chemical descriptors to develop SVM models for reactivity parameters u and v in the U-V scheme has been demonstrated.

Keywords

Genetic algorithm, quantum chemistry, radical copolymerizations, structure-activity relations, support vector machine, transition state

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