(638c) Unraveling Depolymerization and Aromatization Mechanisms in Pt-Catalyzed Polyethylene Upcycling

Developing new and effective methods to manage plastic waste is urgent, as less than 9% of the 370 million tons produced today are recycled. Chemical upcycling, an open-loop process that transforms long-chain polymers into higher-value products through energy-efficient routes, has emerged as a promising strategy to address the plastic crisis. However, optimizing these processes remain challenging, as the fundamental understanding of reaction mechanisms is currently lacking.

This work develops a computational framework to study platinum nanoparticle (Pt NP)-catalyzed polyethylene depolymerization into alkylaromatics. We first employ reactive molecular dynamics (MD) with the ReaxFF force field method to investigate the influence of various Pt NP surface structures on product formation and selectivity, focusing on the less coordinated sites, such as steps and edges represented by higher Miller index facets. To track reaction progress, we develop an automated workflow that identifies chemical species throughout the simulation by assigning van der Waals radii, detecting bonds, and converting molecular fragments to SMILES strings.

Our simulations at elevated temperatures (2000 and 2400 K) show PE chains rapidly breaking down into low-molecular-weight hydrocarbons. Notably, stepped Pt surfaces demonstrated enhanced catalytic activity by producing more aromatic rings and accelerating PE chain breakdown compared to flat surfaces. From our simulations, we elucidate a clear mechanistic pathway: alignment of PE chains to the Pt surface, followed by adsorption and subsequent dehydrogenation and ring closure. We further validated the observed mechanisms in the ReaxFF simulations using first-principles density functional theory (DFT) calculations.

This study advances the mechanistic understanding of polyolefin transformation, contributing to global efforts addressing plastic pollution through chemical upcycling. More broadly, our integrated ReaxFF-DFT approach addresses a methodological gap in computational catalysis, offering a framework for studying complex reactions at interfaces that can be extended to other catalytic systems involving condensed phases and macromolecules.