Complex Flows and Advanced Transport Lab
Our research is built on a single observation: transport in systems with flow-responsive boundaries and material properties cannot be described by classical models, and closing this gap requires new physics across membrane separation, biological flows, and complex mixing.
Direct numerical simulations, coupled multiphysics, and scientific machine learning — all realized on high-performance computing.
Research Program
Thrust I
Classical hemodynamic models predict biological outcomes from instantaneous local conditions. Biology does not work this way — proteins activate, cells damage, and signals propagate based on the accumulated history of mechanical exposure. We build the transport frameworks that make this history physically legible: data-driven models for macromolecular activation, exposure-based cellular damage metrics, and mechanistic descriptions of flow-mediated intercellular signaling.
Thrust II
Functional surface science has historically treated flow as a passive delivery mechanism. This framing misses the dominant physics. Membrane performance, catalytic reaction rates, and surface-mediated separation are governed by bidirectional coupling between local flow structure and surface response — the surface breathes, responds, and feeds back on the flow. Active work on centrifugal reverse osmosis, stimuli-responsive polymer membranes, and flow-history-dependent fouling and polarization.
Shared Foundation
Both thrusts draw from a common methodological foundation: transport physics in regimes where classical closure models fail. Variable-property turbulence, high-Schmidt-number scalar transport, and viscosity-gradient-driven laminarization — each diagnosed through high-fidelity simulation. Near-wall particle dynamics extends this foundation into territory where continuum assumptions fail. This is the physical language both thrusts require, and the credibility that our claims about model failure are not conjectural.
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