Collective behavior of active Brownian particles: From microscopic clustering to macroscopic phase separation

2016 ◽  
Vol 225 (11-12) ◽  
pp. 2287-2299 ◽  
Author(s):  
Thomas Speck
2020 ◽  
Vol 6 (34) ◽  
pp. eaaz1110 ◽  
Author(s):  
Kai Leong Chong ◽  
Jun-Qiang Shi ◽  
Guang-Yu Ding ◽  
Shan-Shan Ding ◽  
Hao-Yuan Lu ◽  
...  

Brownian motion of particles in fluid is the most common form of collective behavior in physical and biological systems. Here, we demonstrate through both experiment and numerical simulation that the movement of vortices in a rotating turbulent convective flow resembles that of inertial Brownian particles, i.e., they initially move ballistically and then diffusively after certain critical time. Moreover, the transition from ballistic to diffusive behaviors is direct, as predicted by Langevin, without first going through the hydrodynamic memory regime. The transitional timescale and the diffusivity of the vortices can be collapsed excellently onto a master curve for all explored parameters. In the spatial domain, however, the vortices exhibit organized structures, as if they are performing tethered random motion. Our results imply that the convective vortices have inertia-induced memory such that their short-term movement can be predicted and their motion can be well described in the framework of Brownian motions.


2014 ◽  
Vol 112 (21) ◽  
Author(s):  
Thomas Speck ◽  
Julian Bialké ◽  
Andreas M. Menzel ◽  
Hartmut Löwen

2021 ◽  
pp. e1902585
Author(s):  
Sophie Hermann ◽  
Daniel de las Heras ◽  
Matthias Schmidt

2021 ◽  
Vol 18 (177) ◽  
Author(s):  
Harvey L. Devereux ◽  
Colin R. Twomey ◽  
Matthew S. Turner ◽  
Shashi Thutupalli

We study the collective dynamics of groups of whirligig beetles Dineutus discolor (Coleoptera: Gyrinidae) swimming freely on the surface of water. We extract individual trajectories for each beetle, including positions and orientations, and use this to discover (i) a density-dependent speed scaling like v ∼ ρ − ν with ν ≈ 0.4 over two orders of magnitude in density (ii) an inertial delay for velocity alignment of approximately 13 ms and (iii) coexisting high and low-density phases, consistent with motility-induced phase separation (MIPS). We modify a standard active Brownian particle (ABP) model to a corralled ABP (CABP) model that functions in open space by incorporating a density-dependent reorientation of the beetles, towards the cluster. We use our new model to test our hypothesis that an motility-induced phase separation (MIPS) (or a MIPS like effect) can explain the co-occurrence of high- and low-density phases we see in our data. The fitted model then successfully recovers a MIPS-like condensed phase for N = 200 and the absence of such a phase for smaller group sizes N = 50, 100.


Soft Matter ◽  
2021 ◽  
Author(s):  
Austin R Dulaney ◽  
John F. Brady

We demonstrate that deep learning techniques can be used to predict motility-induced phase separation (MIPS) in suspensions of active Brownian particles (ABPs) by creating a notion of phase at the...


Soft Matter ◽  
2018 ◽  
Vol 14 (38) ◽  
pp. 7873-7882 ◽  
Author(s):  
Guo-Jun Liao ◽  
Sabine H. L. Klapp

Active Brownian particles can exhibit motility-induced phase separation, in which densely packed clusters coexist with freely moving swimmers. We investigate the impact of active rotation on the coexisting densities and discover a novel state of clockwise vortices.


Sign in / Sign up

Export Citation Format

Share Document