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Prediction of the Qe parameters from transition state structures

Authors

  • Xinliang Yu,

    1. State Key Laboratory of Chemo/Biosensing and Chemometrics, College of Chemistry and Chemical Engineering, Hunan University, Changsha, Hunan 410082, China
    2. College of Chemistry and Chemical Engineering, Hunan Institute of Engineering, Xiangtan, Hunan 411104, China
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  • Ruqin Yu

    Corresponding author
    • State Key Laboratory of Chemo/Biosensing and Chemometrics, College of Chemistry and Chemical Engineering, Hunan University, Changsha, Hunan 410082, China
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State Key Laboratory of Chemo/Biosensing and Chemometrics, College of Chemistry and Chemical Engineering, Hunan University, Changsha, Hunan 410082, China. E-mail: rqyu@hnu.edu.cn

Abstract

The Qe scheme is remarkably useful in interpreting and predicting the reactivity of a monomer in free radical copolymerizations. In the present work, two support vector regression (SVR) models were developed to predict parameters Q and e in the Qe scheme. Quantum chemical descriptors used to build SVR models were calculated, for the first time, from transition state species with structures C1H3—C2HR3• or •C1H2—C2H2R3, formed from vinyl monomer C1H2 C2HR3 + H•. The optimal ν-SVR model of lnQ (C = 130, ν = 0.2, and γ = 1.0) based on 70 monomers has the root mean square (rms) error of 0.336 and correlation coefficient (R) of 0.982. The optimal ε-SVR model of e (C = 1.2, γ = 3, and ε = 10−2) produces rms = 0.259 and R = 0.963. Compared with previous models, the SVM models in this article have better predictive performance. Results of the study suggest that calculating quantum chemical descriptors from the transition state structures to predict parameters Q and e in the Qe scheme is feasible. This investigation encourages the further application of transition state descriptors to other quantitative structure–activity relationships (QSARs). POLYM. ENG. SCI., 53:2151–2158, 2013. © 2013 Society of Plastics Engineers

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