Dynamics of confined suspensions of swimming particles

Abstract

Low Reynolds number direct simulations of large populations of hydrodynamically interacting swimming particles confined between planar walls are performed. The results of simulations are compared with a theory that describes dilute suspensions of swimmers. The theory yields scalings with concentration for diffusivities and velocity fluctuations as well as a prediction of the fluid velocity spatial autocorrelation function. Even for uncorrelated swimmers, the theory predicts anticorrelations between nearby fluid elements that correspond to vortex-like swirling motions in the fluid with length scale set by the size of a swimmer and the slit height. Very similar results arise from the full simulations indicating either that correlated motion of the swimmers is not significant at the concentrations considered or that the fluid phase autocorrelation is not a sensitive measure of the correlated motion. This result is in stark contrast with results from unconfined systems, for which the fluid autocorrelation captures large-scale collective fluid structures. The additional length scale (screening length) introduced by the confinement seems to prevent these large-scale structures from forming.

Particle diffusion in active fluids is non-monotonic in size

“…In their seminal work, Wu and Libchaber 25 experimentally found that D eff increased linearly with c in suspensions of E. coli. Subsequent studies 26,27,[29][30][31][32] have observed that this scaling holds at low concentrations and in the absence of collective motion. In this regime, D eff can be decomposed into additive components as 26,27,[29][30][31][32] where D 0 and D A are the thermal and active diffusivities, respectively.…”

“…Subsequent studies 26,27,[29][30][31][32] have observed that this scaling holds at low concentrations and in the absence of collective motion. In this regime, D eff can be decomposed into additive components as 26,27,[29][30][31][32] where D 0 and D A are the thermal and active diffusivities, respectively. It has been proposed that the active diffusivity D A is a consequence of advection due to far-field interactions with bacteria 26 and may even be higher near walls 26,27 .…”

Active Brownian particles

“…This approach yields some interesting preditions on long-ranged hydrodynamical coupling between different swimmers as well as between cells and surfaces (see e.g. [158,205,7,272,159,276], or a recent review in [206]). However, recent a recent experiments with E. Coli conducted by Drescher et al [86], show that in most cases the effects of long-ranged hydrodynamic interactions are negligible in comparison to the intrinsic stochasticity in the motion of bacteria (i.e.…”

Propulsive force measurements and flow behavior of undulatory swimmers at low Reynolds number

“…[19][20][21][22] Alternatively, a number of studies have focused on the collective behavior of bacteria swarm, both experimentally [23][24][25][26][27] and theoretically. 23,[28][29][30][31][32] Investigations have shown that bacterial suspensions develop transient patterns of coherent locomotion with correlation lengths much larger than the size of individual organisms. 23,26,28 Such collective motion has been used, for example, to induce mixing in microfluidic devices.…”