New method to predict the thermal degradation behavior of polybenzoxazines from empirical data using structure property relationships

Ian Hamerton*, Scott Thompson, Brendan J. Howlin, Corinne A. Stone

*Corresponding author for this work

Research output: Contribution to journalArticle (Academic Journal)peer-review

30 Citations (Scopus)

Abstract

The degradation behavior of five polybenzoxazines is studied and the effect of selected experimental parameters (particle size, heating rate, and atmosphere) on the nature of the degradation pathway is examined. The particle size within the samples (systematically varied in four discrete size ranges: <106, 106-150, 150-250, >250 μm) influences the progress of the early stage in the degradation mechanism (the cleavage of the bridging groups) such that the smaller particles are less stable, but the latter stages of the degradation mechanism remain largely unaffected. In contrast, the change in heating rate (5, 10, 15, 20 K min-1) of the thermogravimetric analysis has little effect on the first step in the degradation mechanism, but has a strong influence on the progress of the ring breakdown mechanism. Molecular simulation is shown to reproduce the thermo-mechanical behavior of the polybenzoxazine of bisphenol A/aniline very well, with the nuances of the glass transition and degradation onset temperatures simulated very closely (e.g., within 10 C of the degradation experiment at a mass loss of 5 wt %). Quantitative structure property relationships are shown to predict the experimental char yields for all the polybenzoxazines studied within the data set, with the calculated values for the polymers based solely on the volume and surface area of the monomer structures.

Original languageEnglish
Pages (from-to)7605-7615
Number of pages11
JournalMacromolecules
Volume46
Issue number19
DOIs
Publication statusPublished - 8 Oct 2013

Fingerprint Dive into the research topics of 'New method to predict the thermal degradation behavior of polybenzoxazines from empirical data using structure property relationships'. Together they form a unique fingerprint.

Cite this