Abstract

.Biological microswimmers often inhabit a porous or crowded environment such as soil. In order to understand how such a complex environment influences their spreading, we numerically study non-interacting active Brownian particles (ABPs) in a two-dimensional random Lorentz gas. Close to the percolation transition in the Lorentz gas, they perform the same subdiffusive motion as ballistic and diffusive particles. However, due to their persistent motion they reach their long-time dynamics faster than passive particles and also show superdiffusive motion at intermediate times. While above the critical obstacle density eta_{c} the ABPs are trapped, their long-time diffusion below eta_{c} is strongly influenced by the propulsion speed v0. With increasing v0, ABPs are stuck at the obstacles for longer times. Thus, for large propulsion speed, the long-time diffusion constant decreases more strongly in a denser obstacle environment than for passive particles. This agrees with the behavior of an effective swimming velocity and persistence time, which we extract from the velocity autocorrelation function.Graphical abstract

Highlights

  • Active matter has been in the focus of intense research for the last decade [1,2,3,4]

  • In this article we studied the dynamics of active Brownian particles in a two-dimensional heterogeneous environment of fixed obstacles modeled by a random Lorentz gas

  • Using Brownian dynamics simulations, we explored how active Brownian particles (ABPs) with different Peclet numbers move at varying obstacle density

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Summary

Introduction

Active matter has been in the focus of intense research for the last decade [1,2,3,4]. We will demonstrate that it performs the same subdiffusive motion as ballistic and diffusive particles close to percolation Besides this universal feature, ABPs explore their environment faster than passive particles due to their persistent motion and reach their long-time dynamics at earlier times. For large propulsion speed, the long-time diffusion constant decreases more strongly in a denser obstacle environment than for passive particles. We rationalize this behavior by studying the velocity autocorrelaton function, which motivates us to introduce an effective swimming velocity and persistence time. 3 we recap the dynamics of a passive Brownian particle in the Lorentz gas and compare it to the ABP in sect.

Active Brownian particle interacting with obstacles
Lorentz model and continuum percolation
System parameters
Influence of the random environment on a passive Brownian particle
Mean squared displacement
Local diffusion coefficient
Influence of the random environment on a microswimmer
Local exponent
Microswimmers in a random Lorentz gas close to the percolation transition
Long-time diffusion and persistent motion
Velocity autocorrelation function
Summary and conclusions
Full Text
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