Predicting Devolatilization in Extrusion: Advancing Polymer Recycling Models

Maintaining consistent quality during polymer extrusion is essential — especially when recycling plastics — because unwanted volatile constituents in the melt can compromise product performance and process stability. One of the less understood but critical steps in extrusion is devolatilization, where volatile organic compounds (VOCs) are removed from the polymer melt in the degassing zone of vented screw extruders.

Accurately predicting devolatilization performance is key to improving quality and enabling wider use of recycled polymers in industry. However, traditional theoretical models often lack sufficient connection with real industrial conditions and experimental data, especially for heterogeneous and complex polymer streams.

The Challenge: Modeling Mass Transport in Devolatilization

In most polymer extrusion processes, devolatilization occurs under either atmospheric or vacuum conditions in partially filled zones of the extruder screw. This process determines how efficiently volatile contaminants are removed from the melt without causing melt loss through degassing openings, a tricky balance that influences extrudate quality.

Existing theoretical models describe devolatilization primarily through simplified mechanisms like bubble-free diffusion. They often fall short when applied to real industrial extrusion with complex flow behaviors, multi-phase conditions, and varied material properties. This gap between theory and practice limits the ability of manufacturers and process engineers to reliably predict performance and optimize operations.

Developing and Validating Predictive Models

To address these challenges, researchers at CHASE, in collaboration with project partners, conducted a comparative study of multiple devolatilization models. These models were evaluated and validated against experimental extrusion data collected from industrial pilot setups, allowing researchers to assess their quantitative accuracy.

By comparing different theoretical approaches and benchmarking them with real process data, the team identified which models more accurately reflect the devolatilization behavior observed in experiments. This comparative analysis provides a clearer foundation for selecting or developing predictive frameworks tailored to industrial conditions.

The study’s outcomes enhance fundamental understanding of mass transport phenomena in the degassing zone and offer a pathway toward more reliable prediction tools. These tools can support process design and control strategies, ultimately aiding manufacturers in achieving consistent product quality and enabling higher adoption of recycled polymers.

Bridging Theory and Industrial Practice

Reliable devolatilization modeling plays a strategic role in polymer recycling and extrusion. As manufacturers increasingly integrate recycled polymers into their production lines to meet sustainability and regulatory goals, predictive models become invaluable assets for process optimization, quality assurance, and reduced waste.

This research demonstrates how validated predictive modeling — grounded in real experimental data — can bridge the gap between fundamental transport phenomena and practical process engineering, advancing both sustainable production and industrial competitiveness.

Project Partners

The work was carried out in collaboration with industrial and academic partners, including EREMA Group GmbH ↗ and Johannes Kepler University Linz (JKU Linz) ↗, within the framework of the COMET research program ↗.

Read the Success Story: Modeling of the Devolatilization Process in an Extruder, Models for the Prediction of the Devolatilization Performance in Extrusion Processes - CHASE PDF ↗