Investigating Polyethylene Solubility for Solvent-Based Recycling: Experiments and SAFT‑γ Mie Predictions

Area of Science:

• Polymer Science
• Chemical Engineering
• Materials Science

Background:

• Solvent-based plastic recycling offers selective polymer dissolution from waste streams.
• Accurate polymer solubility data is essential for process design but currently limited.
• Thermodynamic modeling, like SAFT-γ Mie, can reduce experimental costs and time.

Purpose of the Study:

• To generate extensive polyethylene (PE) solubility data in various solvents across multiple temperatures.
• To assess the predictive accuracy of the SAFT-γ Mie group-contribution (GC) approach for PE solubility.
• To identify effective conventional and bioderived solvents for PE dissolution in recycling.

Main Methods:

• Experimental determination of PE solubility using a polythermal method for four PE samples in ten solvents.
• Thermodynamic modeling using the SAFT-γ Mie group-contribution (GC) approach to predict PE solubility.
• Comparative analysis of experimental and modeling results for solid-liquid and solid-liquid-liquid equilibria.

Main Results:

• High agreement between SAFT-γ Mie predictions and experimental data for PE solubility.
• Decalin, toluene, p-xylene, and mesitylene showed the highest PE solubility.
• Bioderived solvents like limonene, p-cymene, and α-pinene exhibited comparable solubility to aromatic solvents.
• Polymer melting properties significantly influenced PE solubility more than molecular weight.

Conclusions:

• The SAFT-γ Mie GC approach is validated for predicting polymer solubility in complex systems.
• Bioderived solvents are viable, environmentally benign alternatives for polyethylene dissolution.
• This work provides essential data and model validation for advancing solvent-based plastic recycling design.