Microparticle Swarms - Faster Together

Abstract

Colloidal particle swarms can show settling velocities over a thousand times as fast as that of a single particle. The transport of colloidal particles is thus strongly affected by the formation and behaviour of these particle swarms, which could have important implications for the widespread use and prevalence of colloidal particles. Swarming effects may for example pose possibilities and limitations to the use of (colloidal) DNA tracers in various systems. Furthermore, contaminant transport in blue-green porous infrastructure may be greatly enhanced due to the rapid settling of swarms of colloidal contaminants, resulting in rapid spreading of contaminants into the environment.

To better understand colloidal particle swarms in these systems, this thesis studied the effect of particle concentration on the behaviour of colloidal swarms in varying confining geometries.

To this extent, colloidal particles were injected at various concentrations in a macro-model that was suspended in a stagnant water column. The macro-model consisted of three different artificial confining geometries: a smooth fracture, a rough fracture and a pore network. Released swarms were imaged to determine their velocity, width, travelled distance to bifurcation and particle leakage rates from the swarm. In the smooth and rough fracture, the settling velocity of colloidal particle swarms was modelled with the Hadamard & Rybczynski (HR) equation, using the particle leakage rate of the swarm. The average swarm velocity in the pore network was modelled with equations that described the Boycott effect.

In both the smooth and rough fracture, the average velocity of the swarm showed a slight decreasing trend with increasing particle concentration. Presumably, this was caused by the linear relationship between particle concentration and width of the swarm. Consequently, wider swarms experienced lower velocities due to increased hydrodynamic drag forces imposed on the swarm. In the pore network, a strong linear relation was found between the average swarm velocity and the particle concentration. A larger mass of the swarm may have been the cause for this. The travelled distance before bifurcation took place did not show a clear relationship with particle concentration. However, in the performed experiments, swarms did bifurcate at a threshold width in both the smooth and rough fracture. This threshold width increased with concentration.

The HR model did not fit the swarm velocity in the smooth fracture well, because confining forces of the fracture walls enhanced swarm velocity, which was not accounted for by the HR model. Yet, in the rough fracture the HR model did fit well to the observed swarm velocity since the increased drag forces of wall on the swarm counteracted the confining forces. The effect of particle concentration on the average swarm velocity in the pore network was sufficiently well modelled in terms of the Boycott effect.

It was recommended that in future studies laminar flow is introduced to enable better interpretation of results for natural systems. In addition, a more simple pore network geometry provides a more gradual transition to the used complex pore network geometry. This would allow for clearer investigation of swarm behaviour in porous media. Also, more research on swarm behaviour after bifurcation may provide more insight in the longevity of swarm effects.

To determine if colloidal particle swarms may occur in natural fractured media, results of this study should be compared to a field study. Both physical and chemical disturbances may severely hinder colloidal swarms. For both fractured and porous media, injection into a natural sample may provide more insight in behaviour in natural systems. It is however unlikely that swarming effects play a big role in urban colloidal contaminant transport in porous media.