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Using Combined Computational Techniques to Predict the Glass Transition Temperatures of Aromatic Polybenzoxazines

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  • Phumzile Mhlanga
  • Wan Aminah Wan Hassan
  • Ian Hamerton
  • Brendan J Howlin

Abstract

The Molecular Operating Environment software (MOE) is used to construct a series of benzoxazine monomers for which a variety of parameters relating to the structures (e.g. water accessible surface area, negative van der Waals surface area, hydrophobic volume and the sum of atomic polarizabilities, etc.) are obtained and quantitative structure property relationships (QSPR) models are formulated. Three QSPR models (formulated using up to 5 descriptors) are first used to make predictions for the initiator data set (n = 9) and compared to published thermal data; in all of the QSPR models there is a high level of agreement between the actual data and the predicted data (within 0.63–1.86 K of the entire dataset). The water accessible surface area is found to be the most important descriptor in the prediction of Tg. Molecular modelling simulations of the benzoxazine polymer (minus initiator) carried out at the same time using the Materials Studio software suite provide an independent prediction of Tg. Predicted Tg values from molecular modelling fall in the middle of the range of the experimentally determined Tg values, indicating that the structure of the network is influenced by the nature of the initiator used. Hence both techniques can provide predictions of glass transition temperatures and provide complementary data for polymer design.

Suggested Citation

  • Phumzile Mhlanga & Wan Aminah Wan Hassan & Ian Hamerton & Brendan J Howlin, 2013. "Using Combined Computational Techniques to Predict the Glass Transition Temperatures of Aromatic Polybenzoxazines," PLOS ONE, Public Library of Science, vol. 8(1), pages 1-7, January.
  • Handle: RePEc:plo:pone00:0053367
    DOI: 10.1371/journal.pone.0053367
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