Freeze-casting is a popular method to produce biomaterial scaffolds with highly porous structures. The pore structure of freeze-cast biomaterial scaffolds is influenced by processing parameters but has mostly been controlled experimentally. A mathematical model integrating Computational Fluid Dynamics with Population Balance Model was developed to predict average pore size (APS) of 3D porous chitosan-alginate scaffolds and to assess the influence of the geometrical parameters of mold on scaffold pore structure. The model predicted the crystallization pattern and APS for scaffolds cast in different diameter molds and filled to different heights. The predictions demonstrated that the temperature gradient and solidification pattern affect ice crystal nucleation and growth, subsequently influencing APS homogeneity. The predicted APS compared favorably with APS measurements from a corresponding experimental dataset, validating the model. Sensitivity analysis was performed to assess the response of the APS to the three geometrical parameters of the mold: well radius; solution fill height; and spacing between wells. The pore size was most sensitive to the distance between the wells and least sensitive to solution height. This validated model demonstrates a method for optimizing the APS of freeze-cast biomaterial scaffolds that could be applied to other compositions or applications.
Keywords: Computational fluid dynamics; Crystallization; Freeze drying; Modeling; Population balance model; Pore Size; Porous scaffold; Regenerative medicine; Solidification.