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QSPR prediction of thermal decomposition property of non-vinyl polymers having α-amino acids moieties

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Abstract

In the present work, a quantitative structure–property relationship (QSPR) treatment of temperature of five percent of decomposition (T 5) of a number of totally 30 optically active polymers was performed by means of a genetic algorithm-based partial least squares (GA–PLS) and artificial neural network (ANN). Suitable set of molecular descriptors were calculated by dragon package and the important descriptors were selected by GA–PLS methods. These descriptors were served as inputs to generate ANN. After optimization and training of the networks, they were used for the calculation of T 5 for the validation set. By comparing of the results obtained from PLS and ANN models, it can be seen that statistical parameters (Fisher ratio, correlation coefficient, and standard error) of the ANN model are better than PLS one, which indicates that nonlinear model can simulate the relationship between the structural descriptors and T 5 of the investigated macromolecules more accurately.

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Acknowledgments

We wish to express our gratitude to the Research Affairs Division Isfahan University of Technology (IUT), Isfahan, for partial financial support. Further financial support from National Elite Foundation (NEF) and Center of Excellency in Sensors and Green Chemistry Research (IUT) is gratefully acknowledged.

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Authors and Affiliations

  1. Organic Polymer Chemistry Research Laboratory, Department of Chemistry, Isfahan University of Technology, Isfahan, 84156-83111, Islamic Republic of Iran

    Shadpour Mallakpour & Mehdi Hatami

  2. Department of Chemistry, Shahr-e-Rey Branch, Islamic Azad University, Tehran, Iran

    Hassan Golmohammadi

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  1. Shadpour Mallakpour
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  2. Mehdi Hatami
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  3. Hassan Golmohammadi
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Correspondence to Shadpour Mallakpour.

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Mallakpour, S., Hatami, M. & Golmohammadi, H. QSPR prediction of thermal decomposition property of non-vinyl polymers having α-amino acids moieties. Polym. Bull. 70, 715–732 (2013). https://doi.org/10.1007/s00289-013-0906-3

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  • DOI: https://doi.org/10.1007/s00289-013-0906-3

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