<br/>Linear polyethylene is a widely used thermoplastic that is cheap to manufacture due to its simple chemical structure enabling predictable material properties. However, it is difficult to recycle and upcycle efficiently due to a number of constraints which has significant implications in terms of environmental sustainability. Previous research in this area has aimed to find new mechanisms for the thermal degradation of polyethylene such that scission of the molecule results in minimal production of ineffectual side products. In this study, the random scission of linear polyethylene is simulated and characterized through a mesoscopic modeling technique known as energy conserving dissipative particle dynamics (eDPD). The first series of simulations models polymer chains of various lengths at equilibrium to characterize equilibrium properties prior to degradation. Subsequent modeling is performed to characterize the polymer melt at different temperatures with trends similar to available known experimental values. This facilitates the selection of feasible values for the temperature gradient, which will use eDPD and modified segmental repulsive potential (mSRP) to successfully model the distribution of scission products. The degradation rate is differentially induced across the bulk of the polymer melt due to characteristics of the thermal gradient in the vicinity of microwave-absorbing nanosheets. Specifically, the evolution of the molecular weight distribution, radius of gyration, and dispersity of the polymer melt during degradation will be observed. Through the use of Large-scale Atomic/ Molecular Massively Parallel Simulator (LAMMPS) software along with Palmetto Cluster, a new approach to the thermal degradation of polyethylene will be explored and modeled.

Modeling random scission of linear polyethylene via dissipative particle dynamics

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