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Polymers 2016, 8(5), 166; doi:10.3390/polym8050166

Developing (Quantitative Structure Property Relationships) QSPR Techniques to Predict the Char Formation of Polybenzoxazines

1
Department of Chemistry, Faculty of Engineering and Physical Sciences, University of Surrey, Guildford, Surrey, GU2 7XH, UK
2
The Advanced Composites Centre for Innovation and Science, Department of Aerospace Engineering, University of Bristol, Queen’s Building, University Walk, Bristol, BS8 1TR, UK
*
Author to whom correspondence should be addressed.
Academic Editor: Xianqiao (XQ) Wang
Received: 6 November 2015 / Revised: 12 January 2016 / Accepted: 18 April 2016 / Published: 25 April 2016
View Full-Text   |   Download PDF [5498 KB, uploaded 25 April 2016]   |  

Abstract

This study uses the Molecular Operating Environment software (MOE) to generate models to calculate the char yield of polybenzoxazines (PBz). A series of benzoxazine (Bz) monomers were constructed to which a variety of parameters relating to the structure (e.g., water accessible surface, negative van der Waals surface area and hydrophobic volume, etc.) were obtained and a quantitative structure property relationships (QSPR) model was generated. The model was used to generate data for new Bz monomers with desired properties and a comparison was made of predictions based on the QSPR model with the experimental data. This study shows the quality of predictive models and confirms how useful computational screening is prior to synthesis. View Full-Text
Keywords: polybenzoxazines; thermal stability; char formation; mathematical modelling; QSPR polybenzoxazines; thermal stability; char formation; mathematical modelling; QSPR
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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MDPI and ACS Style

Sairi, M.; Howlin, B.; Hamerton, I. Developing (Quantitative Structure Property Relationships) QSPR Techniques to Predict the Char Formation of Polybenzoxazines. Polymers 2016, 8, 166.

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