Particle migration through gels, glasses, and other porous media provides selectivity, storage, and delivery of macromolecules and other particles that are critical to biological cell function, drug delivery, and water filtration. Modeling migration rates of solvent-borne colloids through such materials is thus essential in understanding and engineering the structure-transport relationship. However, most of these materials comprise an amorphously structured porous network not amenable to analytical modeling. Approaches to overcoming this challenge typically bypass interrogating the porous network by abstracting it away via mean-field models or by interrogating the solid features for a coarse estimate of porosity. While such approaches reduce analytical complexity significantly, resulting models cannot reveal interconnectedness of the void network, size-specific permeability, or insight into migration mechanisms. Other approaches aim to extract a network of void paths by approximating a medium as packing of monodisperse spheres and using traditional Voronoi decomposition, giving results that are accurate only when the constituent particles are monodisperse but strongly overpredict the passable size when the medium is made up of size-polydisperse particles, as is the case for colloidal gels, additive manufacturing, soil sediment, to name some examples. We use radical Voronoi decomposition to establish a network backbone of the porous microstructure, which accurately represents morphology for any degree of constituent polydispersity. We present an algorithm for endowing this network with the accurate size and shape and, from it, systematically deducing size-specific accessible branches. The result is a detailed permeability model for porous media of arbitrary microstructure that reveals material morphology, material phase, and size-specific permeability.
Read full abstract