Modelling a Hydrodynamic Instability in Freely Settling Colloidal Gels

TL;DR

This paper develops a phenomenological model to describe the growth and collapse of streamers in settling colloidal gels, validated by simulations and experiments, providing insights into preventing instability in these materials.

Contribution

A new dynamic model for streamer growth in colloidal gels is introduced, combining theory, simulations, and experiments to understand and predict gel failure mechanisms.

Findings

Model exhibits finite-time blowup indicating catastrophic failure.

Simulations agree with theoretical predictions and experimental data.

Stability diagram offers strategies to prevent settling instabilities.

Abstract

Attractive colloidal dispersions, suspensions of fine particles which aggregate and frequently form a space spanning elastic gel are ubiquitous materials in society with a wide range of applications. The colloidal networks in these materials can exist in a mode of free settling when the network weight exceeds its compressive yield stress. An equivalent state occurs when the network is held fixed in place and used as a filter through which the suspending fluid is pumped. In either scenario, hydrodynamic instabilities leading to loss of network integrity occur. Experimental observations have shown that the loss of integrity is associated with the formation of eroded channels, so-called streamers, through which the fluid flows rapidly. However, the dynamics of growth and subsequent mechanism of collapse remain poorly understood. Here, a phenomenological model is presented that describes dynamically the radial growth of a streamer due to erosion of the network by rapid fluid back flow. The model exhibits a finite-time blowup -- the onset of catastrophic failure in the gel -- due to activated breaking of the inter-colloid bonds. Brownian dynamics simulations of hydrodynamically interacting and settling colloids in dilute gels are employed to examine the initiation and propagation of this instability, which is in good agreement with the theory. The model dynamics are also shown to accurately replicate measurements of streamer growth in two different experimental systems. The predictive capabilities and future improvements of the model are discussed and a stability-state diagram is presented providing insight into engineering strategies for avoiding settling instabilities in networks meant to have long shelf lives.