Multiscale predictive model for starch-protein interactions in expanded extruded products
A research collaboration opportunity to develop a multiscale predictive model for the extrusion process of starch-protein mixtures. The model combines physics-based and kinetics-based equations to predict quality attributes such as color, texture, structure, and protein-starch bonding in expanded extrudates, enabling optimized product formulation and processing.
Overview
This research opportunity focuses on understanding and predicting the quality attributes of expanded extruded products made from starch-protein ingredient mixtures. By coextruding starch and protein at varying ratios under different extrusion parameters, the project aims to develop a multiscale predictive model that captures the underlying physico-chemical mechanisms governing product expansion. The model will enable food manufacturers and ingredient companies to predict end-product quality attributes such as color, texture, structure, and protein-starch bonding, supporting more efficient product development and process optimization.
Technical specifications
The research involves a multidisciplinary team combining chemistry, processing engineering, modeling, and sensory science expertise. Key technical activities include:
- Starch-protein binding investigation: A chemist will study the molecular interactions between starch and protein during extrusion and relate these to mechanical properties and glass-transition behavior
- Multiscale modeling approach: A two-level model will be developed, with the first level using statistical modeling to relate product formulations to product structure and quality attributes, and the second level solving porous media physics-based fluid transport equations to simulate expansion
- Process parameter analysis: The model will incorporate extrusion parameters including mechanical properties, temperature, die size, pressure, and plasticizer content
- Sensory evaluation: A trained sensory panel will analyze factors affecting sensory attributes of the extrudates
Technology readiness level
This research is at an early stage, focused on developing the fundamental understanding and predictive modeling capabilities needed to link starch-protein interactions with extrusion processing conditions and final product quality. The project requires collaborative research efforts to validate the multiscale model and demonstrate its predictive accuracy across different ingredient ratios and processing conditions.
About University of Illinois, Urbana-Champaign
The University of Illinois Urbana‑Champaign is a flagship public research university with large‑scale research capacity and a broad academic portfolio. An on‑campus Research Park co‑locates corporate R&D teams and startups with faculty, while the National Center for Supercomputing Applications provides advanced computing and data capabilities for collaboration. Integration with a regional health system and an engineering‑based college of medicine enables clinical translation, and a long‑standing extension network links campus innovation to partners statewide. Research is supported by competitive federal funding from NSF, NIH, DOE, USDA, and DoD. A technology transfer office streamlines IP, licensing, and startups, complemented by incubators and prototyping in the Research Park.
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