Processing behavior evolution of recycled polypropylene: An integrated experimental and Computer-Aided engineering simulation study

• Published in: Physics of fluids (1994) Vol. 37; no. 3
• Main Authors: Estela-García, John E., Hohoff, Paula, Osswald, Tim A.
• Format: Journal Article
• Language: English
• Published: Melville American Institute of Physics 01.03.2025; American Institute of Physics (AIP)
• Subjects: CAE; Computer aided engineering; Computer simulation; Crystallization; Differential scanning calorimetry; Flow simulations; Injection molding; Material characterization methods; Material processing flows; Polymer rheology; Polymers; Polypropylene; Process parameters; Recycling; Reprocessing; Rheological properties; Solid wastes; Thermomechanical analysis; United States > US
• ISSN: 1070-6631; 1089-7666
• DOI: 10.1063/5.0260486

Polypropylene (PP) comprises 21% of global plastics production and 18% of plastics waste, yet less than 1% of solid-waste PP is recycled in the United States (U.S.), representing significant environmental and economic challenges. Mechanical recycling, the most prevalent recycling method, subject's materials to thermomechanical stresses, which typically degrade polymer properties, affecting the quality of polymer products. This study replicates the impact of mechanical recycling through multiple extrusion cycles to examine the effects on PP's processing behavior. Dynamic scanning calorimetry (DSC) measurements showed stable melting behavior across all processing conditions, while crystallization analysis exhibited consistent shifts in kinetic parameters. Rheological characterization demonstrated progressive viscosity reductions through successive cycles, particularly pronounced at elevated reprocessing temperatures. The integration of this experimental data into injection molding simulations showed that recycled PP maintains viable processing characteristics. Our findings establish quantitative correlations between processing history and material behavior, enabling optimization of processing parameters directly rather than relying on trial-and-error approaches. While these results reflect idealized recycling conditions with minimal contamination, they provide a framework for understanding fundamental property evolution during mechanical recycling.