Combining Predictive Diffusion-Based Modeling and In Situ Monitoring for Polyolefin Dissolution: Quantification of Polymer–Solvent Interactions and Kinetics for Recycling Applications

A fundamental model is developed to describe the dissolution of semicrystalline polyolefins in various solvents, which represents a detrimental step of the dissolution-based recycling process. The main steps governing the dissolution are defined to be solvent penetration into the polymer particle through the amorphous region, its swelling, decrystallization of crystalline zones once in contact with solvent, disentanglement of polymer chains from the particle surface, and diffusion of amorphous polymer chains from the particle surface to the solvent, through the boundary layer, consequently leading to a reduction in the particle radius. The model is compared to experimental dissolution data obtained by in situ monitoring using Raman spectroscopy to evaluate the model validity under various operating conditions, such as the solvent type, temperature, or nature of the polymer. Parameter identification was performed to determine the values of both the polymer and the solvent diffusion coefficients as well as the boundary layer thickness and how they are correlated to the varied operating conditions. Polypropylene chains are found to have a diffusivity lower than that of polyethylene due to restricted segmental mobility and lower chain flexibility. As expected, a higher solvent diffusion coefficient in the polymer results in faster dissolution. The effect of temperature on solvent diffusion depends significantly on the solvent type; trichlorobenzene and decane show a sharp increase in diffusivity at higher temperatures, while decalin reaches a diffusion plateau. These findings provide a quantitative framework for understanding solvent effects on polyolefin dissolution, aligning with previous qualitative observations. This work enhances the predictive capabilities for dissolution-based recycling by clarifying the relationships between key parameters and operating conditions.