(10c) Advancements in Moment-Based Modeling: Simulating the Pyrolysis of Vinyl Alcohol-Containing Polymers

Over the past decade, there has been an increased effort towards improving chemical recycling processes, such as pyrolysis. At present, pyrolysis is attractive for single-component feeds, but the diverse composition of feedstocks presents challenges. To design more practical industrial-scale pyrolysis systems, researchers must gain a more detailed understanding of the depolymerization mechanisms. To address this challenge, mechanistic models were constructed using the method of moments (MoM), as it can capture a high level of chemical detail at low computational cost. Using rate laws that consider length-dependent factors, MoM tracks the changes in molecular weight distributions of polymer chains.

This work expands the diversity of polymeric systems that can be modeled using MoM. By incorporating a topological dependence of reaction rates, the mechanisms by which reactive moieties pyrolyze are simulated more accurately. Specifically, this work focused on vinyl alcohol-containing polymers: polyvinyl alcohol (PVA) and ethyl-vinyl alcohol (EvOH), two consumer-grade food packaging plastics.

Both models predict detailed product distributions and simulate mass loss as a function of temperature to compare to experimental TGA results. Subsequently, this work has answered several key mechanistic questions. For example, it is widely accepted that 1,2-dehydration reactions are the primary mechanism for water production. However, this work concludes that the low onset temperature of mass loss could not be rationalized by this reaction alone. Ultimately, these models showed the importance of hydroxyl-assisted 1,2-dehydration.

By combining the MoM with stochastic sequencing functionality, these models bridge the gap between the MoM and a wide range of polymers whose mid-chain chemistry previously made development of detailed kinetic models intractable. They reduce the uncertainty surrounding the thermal degradation mechanism of PVA and EvOH, illuminating the pathways by which high-value products are made. Ultimately, these models can progress chemical recycling by predicting product yields with higher fidelity, guiding optimal pyrolysis reactor design.