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QSPR Analysis of the Patterns Scheme Parameters for the Prediction of Monomer Reactivity Ratios

QSPR Analysis of the Patterns Scheme Parameters for the Prediction of Monomer Reactivity Ratios Two quantitative structure‐property relationship (QSPR) models were developed to correlate radical chemical structure and the reactivity parameters u and v, respectively, of the revised patterns scheme for the prediction of monomers reactivity ratios. The radicals with structure C1H3–C2HR3· (formed from C1H2C2HR3 and H·) were calculated using the UB3LYP density functional theory (DFT) methods with a 6‐31G(d) basis set. The calculated quantum chemical descriptors were used to construct QSPR models for the reactivity parameters (u, v) by applying the genetic algorithm (GA) method, together with multiple linear regression (MLR) analysis. Correlation coefficients for the training sets are 0.941 for the parameter u and 0.947 for the parameter v; correlation coefficients for the test sets are 0.947 for u and 0.934 for v. The results suggest that calculating quantum chemical descriptors from radicals to develop models for parameters u and v is feasible. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Chinese Journal of Chemistry Wiley

QSPR Analysis of the Patterns Scheme Parameters for the Prediction of Monomer Reactivity Ratios

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References (16)

Publisher
Wiley
Copyright
Copyright © 2011 Wiley Subscription Services, Inc., A Wiley Company
ISSN
1001-604X
eISSN
1614-7065
DOI
10.1002/cjoc.201190058
Publisher site
See Article on Publisher Site

Abstract

Two quantitative structure‐property relationship (QSPR) models were developed to correlate radical chemical structure and the reactivity parameters u and v, respectively, of the revised patterns scheme for the prediction of monomers reactivity ratios. The radicals with structure C1H3–C2HR3· (formed from C1H2C2HR3 and H·) were calculated using the UB3LYP density functional theory (DFT) methods with a 6‐31G(d) basis set. The calculated quantum chemical descriptors were used to construct QSPR models for the reactivity parameters (u, v) by applying the genetic algorithm (GA) method, together with multiple linear regression (MLR) analysis. Correlation coefficients for the training sets are 0.941 for the parameter u and 0.947 for the parameter v; correlation coefficients for the test sets are 0.947 for u and 0.934 for v. The results suggest that calculating quantum chemical descriptors from radicals to develop models for parameters u and v is feasible.

Journal

Chinese Journal of ChemistryWiley

Published: Jan 1, 2011

Keywords: ; ; ; ; ;

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