Clogging of particle suspensions in networks

Abstract

In many biological, biomedical and industrial systems, particles are transported via fluids through confined networks, in which clogging can disrupt function. However, we lack a predictive theoretical framework that couples particle transport, suspension rheology and network flow resistance. Here, we develop a model and solution algorithm for particle suspension flow in networks based on vessel-level continuum modelling and particle distribution at nodes connecting vessels. We apply the model to study transport of dense particle suspensions in minimal and physiological biological networks. A key feature of our model is the coupling between particle volume fraction and particle flux: in line with the physics of dense suspensions, each network branch, or vessel, possesses a local carrying capacity for particle transport at an intermediate particle fraction between zero and the maximum packing fraction. If this flux capacity is reached, the vessel becomes flux-limited and particles can accumulate in upstream branches, causing them to enter a high-particle-fraction, high-resistance state that we refer to as 'clogged'. We show that these vessel flux limitations lead to network-level redistribution of particles, which can cause widespread clogging and emergent network-scale heterogeneity. By varying network topology, we find that in some regimes increasing network connectivity does not improve transport: paradoxically, additional pathways can promote clogging and reduce network-level particle flux, analogous to classic results in traffic flow networks. Our results provide a minimal mechanistic framework that links suspension physics, network topology, and transport failure in complex flow networks.