Emergent vortices and phase separation in systems of chiral active particles with dipolar interactions

Abstract

Using Brownian dynamics (BD) simulations we investigate the self-organization of a monolayer of chiral active particles with dipolar interactions. Each particle is driven by both, translational and rotational self-propulsion, and...

Tunable collective dynamics of ellipsoidal Quincke particles

“…Finally, giant number fluctuations are widely observed in an active system. 39,40 However, Fig. 4h shows that the number fluctuations observed is scaled by DN 2 B L 2 .…”

Collective behavior of chiral active particles with anisotropic interactions in a confined space

“…An analysis of C ( r ) is helpful to characterize the spatial ordering of velocity for particles involved in the vortex pattern. 57,62 We evaluate C ( r ) according towhere v ( r ) is the velocity of a particle which is located at a spacing distance r from a reference particle whose velocity reads v (0). Here, C ( r ) has been normalized by the autocorrelation function C (0) = 〈 v (0) 2 〉.…”

“…An analysis of C(r) is helpful to characterize the spatial ordering of velocity for particles involved in the vortex pattern. 57,62 We evaluate C(r) according to…”

“…For example, Klapp et al investigated the self-organization of a monolayer of chiral active particles with dipolar interactions. 57 A wealth of phenomena was revealed including formation of two types of vortices, phase separation, and flocking transitions. Liebchen et al generalized the Vicsek model to describe the collective behavior of polar circle swimmers with local alignment interactions, and they found that circular motion enhances the polarization in the ordered phase (enhanced flocking).…”

Spontaneous trail formation in populations of auto-chemotactic walkers

“…The behaviour of "active" (self-propelled) synthetic particles has been subject of intense research in soft matter and statistical physics, with focus on the motion of individual particles [16,17] and their response to complex environments [18][19][20][21]. Concomitantly, strong emphasis was laid on emerging collective patterns, which include flocking [22], herding [23], vortices [24][25][26], and clustering [27][28][29][30][31][32], just to mention a few. Other than such compact structures, low-dimensional patterns such as isolated trails are relatively underinvestigated.…”