AI-assisted derivation of random chain scission degradation theory for linear polymers having an arbitrary molecular weight distribution

This paper presents an analytical solution for the changes in molecular weight distribution (MWD) of polymers during random degradation, be it due to environmental or other factors. The results and approaches proposed in this work could enable researchers to obtain an analytical expression for the MWD at different stages of random scission, regardless of the initial MWD. This knowledge could enhance the understanding of polymer degradation processes, without requiring mathematical derivation work from the researchers’ side. This is shown in this paper by using Schulz-Zimm distribution as the initial MWD, which is often used to represent the instantaneous MWD of free radical polymerization. A solution for how the MWD evolves during random scission were obtained by the assistance of AI chat tools and verified through symbolic integrator tool and Monte Carlo simulations. This is further extended by showing how the results could be extended to polymers having an arbitrary initial MWD that can be described by any linear combination of the Schulz-Zimm distributions.