Issue 7, 2024

Multi-population dissolution in confined active fluids

Abstract

Autonomous out-of-equilibrium agents or cells in suspension are ubiquitous in biology and engineering. Turning chemical energy into mechanical stress, they generate activity in their environment, which may trigger spontaneous large-scale dynamics. Often, these systems are composed of multiple populations that may reflect the coexistence of multiple species, differing phenotypes, or chemically varying agents in engineered settings. Here, we present a new method for modeling such multi-population active fluids subject to confinement. We use a continuum multi-scale mean-field approach to represent each phase by its first three orientational moments and couple their evolution with those of the suspending fluid. The resulting coupled system is solved using a parallel adaptive level-set-based solver for high computational efficiency and maximal flexibility in the confinement geometry. Motivated by recent experimental work, we employ our method to study the spatiotemporal dynamics of confined bacterial suspensions and swarms dominated by fluid hydrodynamic effects. Our in silico explorations reproduce observed emergent collective patterns, including features of active dissolution in two-population active-passive swarms, with results clearly suggesting that hydrodynamic effects dominate dissolution dynamics. Our work lays the foundation for a systematic characterization and study of collective phenomena in natural or synthetic multi-population systems such as bacteria colonies, bird flocks, fish schools, colloid swimmers, or programmable active matter.

Graphical abstract: Multi-population dissolution in confined active fluids

Supplementary files

Article information

Article type
Paper
Submitted
08 Sep 2023
Accepted
05 Dec 2023
First published
02 Feb 2024
This article is Open Access
Creative Commons BY-NC license

Soft Matter, 2024,20, 1392-1409

Multi-population dissolution in confined active fluids

C. Fylling, J. Tamayo, A. Gopinath and M. Theillard, Soft Matter, 2024, 20, 1392 DOI: 10.1039/D3SM01196H

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