Escape kinetics of self-propelled particles from a circular cavity

Abstract

We numerically investigate the mean exit time of an inertial active Brownian particle from a circular cavity with single or multiple exit windows. Our simulation results witness distinct escape mechanisms depending on the relative amplitudes of the thermal length and self-propulsion length compared to the cavity and pore sizes. For exceedingly large self-propulsion lengths, overdamped active particles diffuse on the cavity surface, and rotational dynamics solely governs the exit process. On the other hand, the escape kinetics of a very weakly damped active particle is largely dictated by bouncing effects on the cavity walls irrespective of the amplitude of self-propulsion persistence lengths. We show that the exit rate can be maximized for an optimal self-propulsion persistence length, which depends on the damping strength, self-propulsion velocity, and cavity size. However, the optimal persistence length is insensitive to the opening windows’ size, number, and arrangement. Numerical results have been interpreted analytically based on qualitative arguments. The present analysis aims at understanding the transport controlling mechanism of active matter in confined structures.

Escape dynamics of a self-propelled nanorod from circular confinements with narrow openings

“…[32][33][34][35][36][37][38][39][40][41] It becomes even more interesting when selfpropelled objects navigate through confined geometries with narrow openings. 42,43 Here, the term self-propelled objects refers to biological or artificial agents that consume energy from the environment or utilize their internal chemical energy to get directed motion in a complex environment. 44,45 Examples include biological entities such as bacteria, 46,47 spermatozoa, 48 insects, and animals 49,50 and synthetic systems such as selfpropelled Janus rods, discs, light-induced active particles, and chemically driven systems.…”

“…45,46,[58][59][60] In recent years, some theoretical and experimental studies have been reported on the quantification of the mean first passage time of the self-propelled particles in confined geometries, such as a Petri dish, pie-wedge shape, and various shaped-confinements with narrow openings. 43,[61][62][63][64][65][66][67] A very recent experimental study reported that the mean first passage times of an active particle rise monotonically as a function of area fraction of the surrounded passive discs (crowders), while their fluctuations exhibit non-monotonic behavior. 61 Debnath et al numerically investigated the mean exit time of an active particle from circular confinement with single or multiple exit windows, and they observed that overdamped active particles spread on the surface of the confinement at extensive selfpropulsion lengths and rotational dynamics govern the escape process.…”

“…61 Debnath et al numerically investigated the mean exit time of an active particle from circular confinement with single or multiple exit windows, and they observed that overdamped active particles spread on the surface of the confinement at extensive self-propulsion lengths and rotational dynamics govern the escape process. 43 A recent numerical study investigated the effect of motility parameters on the narrow escape time of active particles from circular domains. 66 This study compared two paradigmatic models of active motions, namely, run-and-tumble and active Brownian.…”

Driven transport of active particles through arrays of symmetric obstacles

“…Through this mechanism, active particles coexist between two phases of different densities. Conspicuous transport features, unusual collective behaviors, and huge application potential motivate researchers to fully understand diffusion of active particles in crowded environments [39,40], under various types of geometric constraints [41][42][43][44][45][46][47][48][49][50][51][52][53][54] and fluid flow [55][56][57][58][59].…”

Escape dynamics in an anisotropically driven Brownian magneto-system

“…The classical trap model has been generalized to include fluctuations other than thermal fluctuations [3][4][5][6][7]. Such a scenario arises naturally in active gels [8,9], in which embedded tracer particles are subjected to both thermal fluctuations and motor-induced, athermal fluctuations [10], and for active particles [11][12][13][14][15][16][17]. While one models the thermal fluctuations in the usual fashion as white Gaussian noise, the other noise is often described as a colored noise to model the effect of active, athermal fluctuations.…”