Dynamic multiphase imaging and transport characterization

Overview

This research program combines advanced optical imaging with analytical transport modeling to generate dynamic compositional maps of complex multiphase systems. The approach is designed to reveal how chemical species move, transform, and destabilize over time in materials such as foods, pharmaceuticals, and consumer products. By identifying the mechanisms behind instability or degradation, the technology supports better formulation, shelf-life prediction, and quality control.

The core value is the ability to observe transport phenomena at the molecular scale without disrupting the sample. The methods are initially label-free, using natural signals from the sample itself, and can introduce fluorescent labels only if needed.

Technical specifications

Key capabilities:

• Raman microscopy provides spectral fingerprints that distinguish different chemical species, including polymorphs of the same crystalline compound, within a small volume (voxel)
• Fluorescence lifetime imaging (FLIM) and spectral heterogeneity analysis (smFLUSH) extract microenvironment-dependent signatures from single fluorescent molecules
• Fluorescence correlation spectroscopy (FCS) measures diffusion and concentration dynamics at the single-molecule level
• Native autofluorescence of lipids such as arachidonic acid, flavins, and NAD(P)H-bound species enables label-free imaging in many biological and soft-matter systems
• Analytical models of multiphase transport are used to reconcile imaging observations with the underlying physical mechanisms

The approach is flexible: it can be applied to a wide range of sample types and can adapt between label-free and labeled modes depending on the system's optical properties.

Technology readiness level

This is an exploratory research program at an early stage of development. The imaging and modeling methods are well established in the research group, but the integrated workflow for dynamic multiphase transport characterization is still being validated. The next phase involves applying the techniques to a real-world system of interest, identifying the most informative imaging modalities, and reconciling results with transport models. The intended collaboration would support a co-advised PhD student over a multi-year timeframe, with the partner gaining early access to validated methods and workforce development opportunities.