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Multiphysics Numerical Simulation of Supercritical CO 2 Processing in Chitosan Aerogel Beads: Coupled Heat and Mass Transfer With Porosity and Shrinkage Evolution

Jul 2026 · Polymer Engineering & Science · 0 citations · 34 references

Abstract

This study presents a transient multiphysics numerical model for analyzing supercritical CO 2 (scCO 2 ) drying of single chitosan alcogel beads, focusing on coupled heat transfer, solvent diffusion, porosity evolution, and shrinkage deformation. The model integrates Darcy‐based flow behavior, Fickian solvent diffusion, and energy conservation equations to resolve interactions between temperature, pressure, and solvent concentration fields under fixed operating conditions. A finite‐element framework was implemented and validated against experimental solvent removal data reported in the literature at 40°C and 15 MPa, showing strong agreement with drying kinetics trends. Results indicate that the temperature inside the bead remains nearly uniform throughout the process, reflecting low Biot number conditions where internal heat transfer resistance is negligible. Solvent removal follows two characteristic stages: an initial constant‐rate period dominated by external CO 2 solvent mass transfer, followed by a falling‐rate regime controlled by internal diffusion resistance. Parametric analysis demonstrates that increasing operating pressure enhances CO 2 density and solvent solubility, accelerating drying and reducing total process time by approximately 28%, while inducing moderate pore compression. The model predicts porosity reduction from 0.85 to approximately 0.68 and volumetric shrinkage of about 25%, consistent with reported experimental observations. Additional simulations show that both effective solvent diffusivity and initial porosity strongly influence drying kinetics. A qualitative comparison with conventional drying techniques confirms that scCO 2 drying provides an optimal balance between structural preservation and processing time. The developed model offers a robust predictive tool for optimizing aerogel drying processes.

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