(724d) The Influence of Structure-Property Relationships in Polyethylene Terephthalate on Glycolytic Deconstruction

Efficient recycling of plastics requires a thorough understanding of complex deconstruction mechanisms intertwined with the structure-property relationships of these feedstocks for optimizing the conversion. Continuum models are limited to tracking the overall decomposition of lumped polymeric species and the temporal evolution of products and provide little information on the influence of the structure and morphological properties, such as crystallinity, on the depolymerization mechanisms. Tracking specific chain sequences and changes in the morphology is important when studying glycolytic deconstruction at temperatures ranging between the glass transition temperature and the melting point of semicrystalline polymers, like polyethylene terephthalate (PET). This study aims to develop a detailed Kinetic Monte Carlo (kMC) framework to gain insights into the structure-property relationships of PET and the impact on glycolytic deconstruction.

In this work, the initial chain length distribution of PET is determined by assuming a Schulz-Flory distribution function. The spherulitic morphology is then defined by the distributions of tails, ties, loops, and crystalline stems present in the PET chains, which are generated using random-walk simulations based on their probabilities of formation. KMC simulations of catalytic PET glycolysis at discrete time steps for reaction temperatures between 150-190 ^oC suggest a competition between the random, chain scission and repolymerization reactions at different reaction timescales. Mapping the reactions and distributions suggests that interlamellar amorphous domains like tie chains and loops undergo sequential random scission forming tails and disrupt the spherulitic morphology during the initial phase of glycolytic deconstruction. While the end chain scission of free amorphous domains and tails resulted in BHET monomer, it has been observed that the reactivity of crystalline stems governs the monomer yield at longer reaction times. Such frameworks are promising in developing predictive models for the solvent-based depolymerization of condensation polymers and gaining insights into the structure-property relationships.