Poster: Kinetic modeling of polyethylene hydrogenolysis for plastic waste recycling

Hydrogenolysis offers a method to recycle plastic waste by converting it into chemicals like liquid fuels, lubricants, and waxes. While experiments show that hydrogenolysis can break down polyethylene into short hydrocarbon chains, the process has low selectivity for fuels, with methane being the dominant product. Here, we use kinetic Monte Carlo simulations and machine learning to identify elementary steps from density functional theory calculations and experimental data on polyethylene hydrogenolysis [1, 2]. Preliminary data indicates accelerated methane conversion with central cleaving at every chain length, compared to terminal cleaving at equivalent locations and rates. Differing product distributions result from varying cleavage sites along the polymer, suggesting an optimal chain length that maximizes desired product yield. This approach bridges the gap between macroscopic processes and microscopic reaction mechanisms, providing insights into how reaction conditions affect the kinetics of hydrocarbon formation.

[1] Rorrer, J. E., et al. JACS Au 2020

[2] Chen, L., et al. React. Chem. Eng. 2022