Correlating processing variables to material properties in recycled polypropylene: A data‐driven approach DOI Creative Commons

John E. Estela‐García,

Allen Jonathan Román, Tim A. Osswald

et al.

SPE Polymers, Journal Year: 2025, Volume and Issue: 6(2)

Published: April 1, 2025

Abstract Polypropylene (PP) is one of the most widely used plastics, yet its recycling remains limited, with less than 1% solid waste PP being reprocessed. Mechanical through extrusion practical method, but inconsistent reprocessing conditions introduce variability in material properties. While temperature, screw speed, and residence time influence thermomechanical stress applied during reprocessing, there are no standardized guidelines for optimizing these parameters. This study examines how factors shape properties recycled PP, using designed to mimic post‐industrial (PIR) scrap. Residence was measured colorimetric tracking correlated molecular weight, viscosity, mechanical over multiple cycles. Data‐driven modeling, including response surface methodology, support vector machines, artificial neural networks, identified processing temperature as dominant factor degradation, followed by time. remained stable, while viscosity decreased predictably increasing By linking property evolution, this provides a method optimize parameters reduce PP. These findings help manufacturers improve process control, making more predictable reuse manufacturing. Highlights Study PIR‐quality without additives or compatibilizers. analysis shows drives changes. Mark‐Houwink enables quick weight checks quality control. Models predict rheological shifts reprocessing. Optimized minimize degradation recycling.

Language: Английский

Correlating processing variables to material properties in recycled polypropylene: A data‐driven approach DOI Creative Commons

John E. Estela‐García,

Allen Jonathan Román, Tim A. Osswald

et al.

SPE Polymers, Journal Year: 2025, Volume and Issue: 6(2)

Published: April 1, 2025

Abstract Polypropylene (PP) is one of the most widely used plastics, yet its recycling remains limited, with less than 1% solid waste PP being reprocessed. Mechanical through extrusion practical method, but inconsistent reprocessing conditions introduce variability in material properties. While temperature, screw speed, and residence time influence thermomechanical stress applied during reprocessing, there are no standardized guidelines for optimizing these parameters. This study examines how factors shape properties recycled PP, using designed to mimic post‐industrial (PIR) scrap. Residence was measured colorimetric tracking correlated molecular weight, viscosity, mechanical over multiple cycles. Data‐driven modeling, including response surface methodology, support vector machines, artificial neural networks, identified processing temperature as dominant factor degradation, followed by time. remained stable, while viscosity decreased predictably increasing By linking property evolution, this provides a method optimize parameters reduce PP. These findings help manufacturers improve process control, making more predictable reuse manufacturing. Highlights Study PIR‐quality without additives or compatibilizers. analysis shows drives changes. Mark‐Houwink enables quick weight checks quality control. Models predict rheological shifts reprocessing. Optimized minimize degradation recycling.

Language: Английский

Citations

0