A novel mechanistic modelling framework for high-density polyethylene pyrolysis is presented, utilising absorbing Markov chains to describe intramolecular hydrogen shifts as transitional states. The model generates probability mass functions to predict the formation of specific secondary radicals, allowing for efficient description of complex reaction degeneracy. Numerical simulations show good agreement with literature and experimental data, providing insights into the statistical nature of random scission and backbiting reaction pathways. Compared to traditional method-of-moments and kinetic Monte Carlo models, this modelling framework is unique in its ability to capture all structural detail of the pyrolysis reaction while remaining computationally efficient, demonstrating a 70–91% reduction in wall-clock execution time compared to traditional kMC models at common pyrolysis temperatures. Moreover, it is generalisable to other free radical reaction pathways beyond polyethylene pyrolysis, making it a potentially valuable modelling approach for exploring the behaviour of a wide range of chemical systems.
Viet et al. (Mon,) studied this question.