- Background
- What we're looking for
- What we can offer you
- Q&A
Many confectionery products rely on carefully designed multi-phase structures to deliver specific textures, mouthfeel, and sensory experiences. These systems often combine components with different compositions and physical properties, such as fat-based phases, aqueous phases, and particulate inclusions. Increasingly, these products are being reimagined to deliver indulgence with a more mindful nutritional profile, incorporating functional ingredients that can replicate or enhance the role traditionally played by sugar, often introducing additional complexity in structure and behavior.
Over time, these multi-phase systems can become unstable due to the migration of components such as water and lipids between phases. Importantly, component transport in these systems is often not governed by simple Fickian diffusion. Migration can be coupled to secondary time-dependent events—e.g., fat crystallization/polymorphic transitions, dissolution–recrystallization of solutes, glass transition–driven mobility changes, swelling or collapse of matrices, capillary flow through evolving pore networks, or interfacial restructuring—resulting in anomalous (non‑Fickian) kinetics and spatially heterogeneous pathways at mesoscopic length scales.
This can lead to texture degradation, softening or hardening of layers, loss of structural integrity, and broader changes in product performance. While individual components are typically well understood, their behavior can change significantly once combined, as interactions at interfaces and local variations within the structure drive migration phenomena that are not well captured by existing measurement approaches or predictive models, which often rely on averaged properties or simplified systems. In addition, many of these frameworks have been developed around traditional sugar-based systems and may not accurately reflect the behavior of newer ingredient systems used to deliver reduced-sugar products.
A deeper understanding of how water and lipids are distributed, interact, and migrate within complex, multi-phase structures, along with improved tools to measure and model these phenomena at relevant spatial scales, would enable more intentional design of food systems. This would support greater control over texture, stability, and performance, and unlock the development of new and more complex product formats.
We are seeking solutions that enable the prediction, measurement, and/or control of water and fat migration in multi-phase confectionery systems, including novel modeling tools, analytical techniques, and material or structural strategies to manage these phenomena. We are particularly interested in approaches that capture spatial variability within complex systems (e.g., mapping distribution across phases and interfaces), and in predictive models that move beyond traditional sugar-based frameworks to reflect the behavior of alternative ingredients such as sugar alcohols, soluble fibers, and other sugar-replacement ingredients, and their interactions within real multi-phase structures.
- Mechanistic or hybrid predictive models (physics-based, data-assisted, or multiscale) that incorporate spatial heterogeneity, interfaces, and coupling between transport and time-dependent structure evolution (e.g., crystallization, glass transition, swelling/collapse)
- Advanced analytical/imaging methods to map phase distribution and local mobility of water and lipids over time (not just bulk averages), ideally capturing interfacial regions and inclusions
- Methods to quantify and model non‑Fickian/anomalous transport, including identification of rate-limiting steps and transitions in kinetic regime
- Barrier/coating strategies, structural design, and formulation approaches
- Enables prediction, measurement, or control of water and/or fat migration in multi-phase systems, with relevance or adaptability to food applications
- Clear mechanism or scientific basis by which the approach addresses migration phenomena
- For modeling approaches – must be predictive beyond curve-fitting: demonstrates either (i) mechanistic coupling (transport + phase/structure evolution) or (ii) validated prediction across at least two compositions/structures or conditions such as relative humidity (RH), temperature cycling, and shear history
- For modeling approaches – accounts for coupling phenomena relevant to multi-phase foods (e.g., crystallization, glass transition, capillary flow, sorption hysteresis, interfacial effects) and/or explicitly justifies when Fickian assumptions are valid
- Demonstrates spatiotemporal mapping of water/fat distribution (2D/3D) with quantification (not only qualitative images)
- Provides a model that can predict migration kinetics under at least two stressors (e.g., temperature cycling + RH gradient, or composition + processing history)
- Links observed migration to microstructure evolution (e.g., fat crystal network coarsening, pore formation, matrix vitrification) and shows how that changes transport pathways
- Demonstrates potential to improve product stability, texture retention, or shelf life, either by enhancing understanding of migration phenomena or enabling their control
- Solutions limited to bulk/averaged measurements only without spatial resolution (unless clearly justified)
- Models that are purely empirical fits with no validation across conditions/compositions
- Approaches requiring unrealistic sample preparation that fundamentally changes structure (unless framed as a model system)
The Q&A is now closed.
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