Hostname: page-component-6766d58669-mzsfj Total loading time: 0 Render date: 2026-05-22T18:29:21.892Z Has data issue: false hasContentIssue false

Confinement-induced spreading and fingering of suspensions

Published online by Cambridge University Press:  19 May 2025

Rui Luo
Affiliation:
Engineering Science and Applied Mathematics, Northwestern University, Evanston, IL, USA
Maxwell Marshall
Affiliation:
SICK Sensor Intelligence, Minneapolis, MN, USA
Zilong He
Affiliation:
Department of Mechanical Engineering, University of Minnesota, Minneapolis, MN, USA
Li Wang
Affiliation:
School of Mathematics, University of Minnesota, Minneapolis, MN, USA
Sungyon Lee*
Affiliation:
Department of Mechanical Engineering, University of Minnesota, Minneapolis, MN, USA
*
Corresponding author: Sungyon Lee, sungyon@umn.edu

Abstract

Viscous fingering, a classic hydrodynamic instability, is governed by the the competition between destabilising viscosity ratios and stabilising surface tension or thermal diffusion. We show that the channel confinement can induce ‘diffusion’-like stabilising effects on viscous fingering even in the absence of interfacial tension and thermal diffusion, when a clear oil invades the mixture of the same oil and non-colloidal particles. The key lies in the generation of long-range dipolar disturbance flows by highly confined particles that form a monolayer inside a Hele-Shaw cell. We develop a coarse-grained model whose results correctly predict universal fingering dynamics that is independent of particle concentrations. This new mechanism offers insights into manipulating and harnessing collective motion in non-equilibrium systems.

Information

Type
JFM Papers
Creative Commons
Creative Common License - CCCreative Common License - BY
This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted re-use, distribution and reproduction, provided the original article is properly cited.
Copyright
© The Author(s), 2025. Published by Cambridge University Press
Figure 0

Figure 1. (a) Schematic of the experimental set-up: a 2-D Hele-Shaw cell consisting of two rectangular glass plates that are separated by a thin gap. The images of flow patterns are captured from above using a CMOS camera, as the clear oil invades the particle–oil mixture. (b) The time-sequential experimental images at $\phi _i = 10\, \%$ show the gradual widening of fingers over time in a single experiment. (c) The experimental images at $\hat {t}=40\,{\textrm s}$ show the increase in the critical wavelength $\lambda _c$ as the initial concentration $\phi _i$ is increased: $\phi _i=5\, \%$, $15\, \%$, $35\, \%$. The solid line represents the location of the side wall.

Figure 1

Figure 2. (a) Space–time diagram illustrating the number density $\rho _0$ measured and averaged over the channel width from an experiment at $\phi _i = 25\, \%$ or $\rho _i = 1.13\,{\textrm{mm}}^{-2}$. The colour scale indicates the local number density. The rarefaction region (bounded by dashed lines) is characterised by a gradual increase in $\rho _0$. (b) We plot $\rho _0$ measured from the experiments at $\phi _i = 5\, \%, 10\, \%, 15\, \%, 25\, \%$ as a function of $\hat {X}/\hat {t}$, which reveals the self-similarity of our data and two distinct regions. The rarefaction region, exhibiting a positive slope, is influenced by the system’s confinement parameters ($\kappa$ and $S$), while the uniform region is set by $\phi _i$. The colour of each symbol corresponds to different values of $\phi _i$, with the darker shade indicating later dimensional times (see the colourmaps in (b)). (c) The dimensionless number density profiles $c$ from all experiments collapse onto a single rarefaction solution curve, consistent with the predictions of the leading-order equation (dashed line).

Figure 2

Figure 3. (a) The plot of the growth rate $\sigma$ versus the wavenumber $k$. The growth rate varies non-monotonically with $k$, and is positive across a range of wavenumbers. Over time, the critical wavenumber associated with the peak growth rate exhibits a decay. (b) The plot of the critical wavelength $\lambda _c$ over dimensionless time $t$ from the simulations and the experiments; $\lambda _c$ from the simulations increases over $t$. Given the universality of the derived equation, the critical wavelengths from different experiments are expected to converge into a single curve upon non-dimensionalisation. The error bars associated with the experimental data reflect the spatial variability of finger widths in the rarefaction region for each experiment. (c) We include the experimental images from three experiments ($\phi _i=5\, \%,15\, \%,25\, \%$) at $t=12$ (or three separate dimensional times). The three images exhibit similar fingering patterns.

Figure 3

Figure 4. (a) Comparative simulation results between the comprehensive model (4.3) and the simplified physical model (4.5). The simplified model initially fails to capture the system’s instability but converges to a similar constant maximum growth rate over long times. It also accurately predicts the broadening of the wavelength, or equivalently the decrease in $k_c$, as observed in the full model. (b) To represent the physical meaning of $I_1$, we include the schematic of the perturbed line of particles (green curve) affecting a test particle (red circle) placed at a distance $\tilde {x}$ away from it. (c) For given $\tilde {x}$, $I_1$ is negative for all $k$, and its magnitude reaches a maximum at $k=1/\tilde {x}$. The wavenumber selection is influenced by the cumulative impact of all perturbed lines within the expanding rarefaction region.

Figure 4

Figure 5. (a) The plot of the width-averaged intensity $G_y(\hat {X})$ as a function of $\hat {X}$ highlights the rarefaction region inside the cell. (b) We focus on the small region around the rarefaction region to highlight the variations of $G$ in $\hat {y}$, corresponding to the emergent fingers. (c) We turn the original image into a binary image via thresholding (dyed oil in black), from which we extract $\lambda _c$.

Figure 5

Figure 6. The maximum growth rate ($\sigma _{{max}}(t)$) and critical wavenumber ($k_c$) over time based on versions 1, 2, 3 of (4.3).

Supplementary material: File

Luo et al. supplementary material movie

The experiments of oil invasion into a 2D suspension at two different particle concentrations.
Download Luo et al. supplementary material movie(File)
File 2.3 MB