Highly Filled Biocomposites, Characterization, Processing and Modeling
Doktorsavhandling, 2025
The demand for natural fiber-reinforced polymer composites is growing worldwide, driven by cost efficiency and sustainability goals. Wood fiber polymer composites (WPCs) show strong potential, but conventional plastic-based processing methods limit their performance. Understanding WPC flow behavior through experimental and numerical approaches is essential to address these challenges.
This PhD research focused on the processing, characterization, and modeling of WPCs, especially in single-screw extrusion. Using an inline visualization setup and 2D Fourier transforms, we studied flow instabilities and found that higher screw speeds could lead to more stable extrudates, unlike some neat polymers. Factors such as fiber content, moisture, and size were also analyzed, leading to a proposed stability criterion to predict melt instabilities. Machine learning further helped detect and classify instability patterns, showing promising results.
Extrusion modeling, supported by capillary/rotational rheometry and microscopy, provided insight into melt flow and fiber orientation. The Folgar-Tucker model, coupled with fluid dynamics, accurately predicted orientation, confirmed by SEM and pressure data.
In the final phase, we developed shear-induced, oriented wood fiber nanocomposites with significantly enhanced thermal conductivity and anisotropy, achieving a 2239% boost along the flow and 240% perpendicular to the flow, highlighting their industrial potential. This research combines scientific insight with practical methods, advancing renewable polymer composite manufacturing.
This PhD research focused on the processing, characterization, and modeling of WPCs, especially in single-screw extrusion. Using an inline visualization setup and 2D Fourier transforms, we studied flow instabilities and found that higher screw speeds could lead to more stable extrudates, unlike some neat polymers. Factors such as fiber content, moisture, and size were also analyzed, leading to a proposed stability criterion to predict melt instabilities. Machine learning further helped detect and classify instability patterns, showing promising results.
Extrusion modeling, supported by capillary/rotational rheometry and microscopy, provided insight into melt flow and fiber orientation. The Folgar-Tucker model, coupled with fluid dynamics, accurately predicted orientation, confirmed by SEM and pressure data.
In the final phase, we developed shear-induced, oriented wood fiber nanocomposites with significantly enhanced thermal conductivity and anisotropy, achieving a 2239% boost along the flow and 240% perpendicular to the flow, highlighting their industrial potential. This research combines scientific insight with practical methods, advancing renewable polymer composite manufacturing.
fiber orientation
machine learning.
extrusion
Wood polymer composites (WPCs)
modelling
thermal conductivity
rheology
surface insta-bility
Virtual Development Laboratory (VDL), Chalmers Tvärgata 4C
Opponent: Prof. Denis Rodrigue, Department of Chemical Engineering, Université Laval, Canada
Författare
Sajjad Pashazadehgaznagh
Chalmers, Industri- och materialvetenskap, Konstruktionsmaterial
Mapping surface defects in highly-filled wood fiber polymer composite extrusion from inline spectral analysis
Composites Science and Technology,;Vol. 242(2023)
Artikel i vetenskaplig tidskrift
Sajjad Pashazadeh, Arvindh Seshadri Suresh, Stephen Hall, Tobias Moberg, Anders Brolin, Roland Kádár. "A new stability criterion for surface instabilities in wood polymer composites extrusion".
Sajjad Pashazadeh, Valentina Matovic, Tobias Moberg, Anders Brolin, Fang Liu, Roland Kádár. " Revisiting surface tearing extrusion flow instabilities through machine learning".
Predicting orientation in extruded wood polymer composites
Physics of Fluids,;Vol. 36(2024)
Artikel i vetenskaplig tidskrift
Sajjad Pashazadeh, Viney Ghai, Tobias Moberg, Anders Brolin, Kim Nygård, Ann Terry, Roland Kádár. "High Thermal Conductivity in Anisotropic Wood Fiber–PLA Composites Enhanced with Hexagonal Boron Nitride.
När industrin strävar efter grönare och billigare material får trä-polymerkompositer (WPC), en blandning av träfibrer och plast, allt mer uppmärksamhet. Men föråldrade plastbearbetningsmetoder begränsar deras potential.
Min doktorandforskning fokuserade på att förbättra tillverkningen av högfyllda WPC:er, särskilt genom enskskruvsextrudering. Med hjälp av en specialbyggd visualiseringsuppställning och avancerad analys upptäckte jag att högre skruvhastigheter faktiskt kan stabilisera flödet – till skillnad från vid ren plast. Vi identifierade också hur fiberinnehåll, fukt och storlek påverkar stabiliteten, och utvecklade en modell för att förutsäga flödesproblem. För att ta det ett steg längre använde jag maskininlärning för att klassificera olika typer av flödesinstabiliteter, vilket möjliggör effektivare övervakning av processen.
Genom att kombinera experiment och modellering fick vi även insikt i hur träfibrer orienterar sig under bearbetningen. I det sista steget skapade vi orienterade träfiber-nanokompositer med upp till 22× bättre värmeledningsförmåga än konventionell plast – vilket visar enorm potential för grönare och högpresterande material.
Denna forskning bygger en bro mellan vetenskap och industri, och driver utvecklingen av framtidens förnybara komposittillverkning framåt.
Min doktorandforskning fokuserade på att förbättra tillverkningen av högfyllda WPC:er, särskilt genom enskskruvsextrudering. Med hjälp av en specialbyggd visualiseringsuppställning och avancerad analys upptäckte jag att högre skruvhastigheter faktiskt kan stabilisera flödet – till skillnad från vid ren plast. Vi identifierade också hur fiberinnehåll, fukt och storlek påverkar stabiliteten, och utvecklade en modell för att förutsäga flödesproblem. För att ta det ett steg längre använde jag maskininlärning för att klassificera olika typer av flödesinstabiliteter, vilket möjliggör effektivare övervakning av processen.
Genom att kombinera experiment och modellering fick vi även insikt i hur träfibrer orienterar sig under bearbetningen. I det sista steget skapade vi orienterade träfiber-nanokompositer med upp till 22× bättre värmeledningsförmåga än konventionell plast – vilket visar enorm potential för grönare och högpresterande material.
Denna forskning bygger en bro mellan vetenskap och industri, och driver utvecklingen av framtidens förnybara komposittillverkning framåt.
As industries push for greener, cheaper materials, wood-polymer composites (WPCs), a mix of wood fibers and plastics are gaining attention. But outdated plastic processing methods limit their potential.
My PhD focused on improving how highly filled WPCs are made, especially through single-screw extrusion. Using a custom visualization setup and advanced analysis, I found that higher screw speeds can actually stabilize flow, unlike in neat plastics. We also identified how fiber content, moisture, and size affect stability, and developed a model to predict flow issues. To go further, I used machine learning to classify different types of flow instabilities, enabling more efficient process monitoring.
By combining experiments and modeling, we also gained insight into how wood fibers align during processing. In the final stage, we created oriented wood fiber nanocomposites with up to 22× better thermal conductivity than conventional plastics showing huge potential for greener, high-performance materials.
This research bridges science and industry, pushing forward the future of renewable composite manufacturing.
My PhD focused on improving how highly filled WPCs are made, especially through single-screw extrusion. Using a custom visualization setup and advanced analysis, I found that higher screw speeds can actually stabilize flow, unlike in neat plastics. We also identified how fiber content, moisture, and size affect stability, and developed a model to predict flow issues. To go further, I used machine learning to classify different types of flow instabilities, enabling more efficient process monitoring.
By combining experiments and modeling, we also gained insight into how wood fibers align during processing. In the final stage, we created oriented wood fiber nanocomposites with up to 22× better thermal conductivity than conventional plastics showing huge potential for greener, high-performance materials.
This research bridges science and industry, pushing forward the future of renewable composite manufacturing.
Styrkeområden
Produktion
Materialvetenskap
Ämneskategorier (SSIF 2025)
Strömningsmekanik
Maskinteknik
Materialteknik
Kompositmaterial och kompositteknik
Pappers-, massa- och fiberteknik
Infrastruktur
Chalmers strömningslaboratorium
Chalmers materialanalyslaboratorium
ISBN
978-91-8103-199-7
Doktorsavhandlingar vid Chalmers tekniska högskola. Ny serie: 5657
Utgivare
Chalmers
Virtual Development Laboratory (VDL), Chalmers Tvärgata 4C
Opponent: Prof. Denis Rodrigue, Department of Chemical Engineering, Université Laval, Canada