Active Brownian particle

An active Brownian particle (ABP) is a model of self-propelled motion in a dissipative environment. ^{[1] [2] [3]} It is a nonequilibrium generalization of a Brownian particle.

The self-propulsion results from a force that acts on the particle's center of mass and points in the direction of an intrinsic body axis (the particle orientation). ^[3] It is common to treat particles as spheres, though other shapes (such as rods) have also been studied. ^{[4] [5]} Both the center of mass and the direction of the propulsive force are subjected to white noise, which contributes a diffusive component to the overall dynamics. In its simplest version, the dynamics is overdamped and the propulsive force has constant magnitude, so that the magnitude of the velocity is likewise constant (speed-up to terminal velocity is instantaneous).

The term active Brownian particle usually refers to this simple model ^[1] and its straightforward extensions, though some authors have used it for more general self-propelled particle models. ^{[5] [6]}

Equations of motion

Mathematically, an active Brownian particle is described by its center of mass coordinates ${\displaystyle \mathbf {r} }$ and a unit vector ${\displaystyle {\hat {\mathbf {n} }}}$ giving the orientation. In two dimensions, the orientation vector can be parameterized by the 2D polar angle ${\displaystyle \theta }$, so that ${\displaystyle {\hat {\mathbf {n} }}=(\cos \theta ,\sin \theta )}$. The equations of motion in this case are the following stochastic differential equations:

${\displaystyle {\begin{aligned}{\dot {\mathbf {r} }}&=v_{0}{\hat {\mathbf {n} }}-(m\xi )^{-1}\nabla V(\mathbf {r} )+{\sqrt {2D_{t}}}\,{\boldsymbol {\eta }}_{\text{trans}}(t)\\{\dot {\theta }}&={\sqrt {2D_{r}}}\,\eta _{\text{rot}}(t).\end{aligned}}}$

where

${\displaystyle {\begin{aligned}\langle \eta _{\text{rot}}(t)\rangle &=0;\qquad \langle \eta _{\text{rot}}(t)\eta _{\text{rot}}(t')\rangle =\delta (t-t')\\\langle {\boldsymbol {\eta }}_{\text{trans}}(t)\rangle &={\boldsymbol {0}};\qquad \langle {\boldsymbol {\eta }}_{\text{trans}}(t){\boldsymbol {\eta }}_{\text{trans}}^{\intercal }(t')\rangle =\mathbf {I} \delta (t-t')\end{aligned}}}$

with ${\displaystyle \mathbf {I} }$ the 2×2 identity matrix. The terms ${\displaystyle {\boldsymbol {\eta }}_{\text{trans}}(t)}$ and ${\displaystyle \eta _{\text{rot}}(t)}$ are translational and rotational white noise, which is understood as a heuristic representation of the Wiener process. Finally, ${\displaystyle V(\mathbf {r} )}$ is an external potential, ${\displaystyle m}$ is the mass, ${\displaystyle \xi }$ is the friction, ${\displaystyle v_{0}}$ is the magnitude of the self-propulsion velocity, and ${\displaystyle D_{t}}$ and ${\displaystyle D_{r}}$ are the translational and rotational diffusion coefficients. ^[7]

The dynamics can also be described in terms of a probability density function ${\displaystyle f(\mathbf {r} ,\theta ,t)}$, which gives the probability, at time ${\displaystyle t}$, of finding a particle at position ${\displaystyle \mathbf {r} }$ and with orientation ${\displaystyle \theta }$. By averaging over the stochastic trajectories from the equations of motion, ${\displaystyle f(\mathbf {r} ,\theta ,t)}$ can be shown to obey the following partial differential equation:

${\displaystyle {\frac {\partial f}{\partial t}}+v_{0}{\hat {n}}\cdot \nabla f=(m\xi )^{-1}\nabla \cdot (\nabla V(\mathbf {r} )\,f)+D_{r}{\frac {\partial ^{2}f}{\partial \theta ^{2}}}+D_{t}\nabla ^{2}f}$

Behavior

See also: Clustering of self-propelled particles

For an isolated particle far from boundaries, the combination of diffusion and self-propulsion produces a stochastic (fluctuating) trajectory that appears ballistic over short length scales and diffusive over large length scales. The transition from ballistic to diffusive motion is defined by a characteristic length ${\displaystyle \ell =v_{0}/D_{r}}$, called the persistence length. ^[2]

In the presence of boundaries or other particles, more complex behavior is possible. Even in the absence of attractive forces, particles tend to accumulate at boundaries. Obstacles placed within a bath of active Brownian particles can induce long-range density variations and nonzero currents in steady state. ^{[8] [9]}

Sufficiently concentrated suspensions of active Brownian particles phase separate into a dense and dilute regions. ^{[10] [11]} The particles' motility drives a positive feedback loop, in which particles collide and hinder each other's motion, leading to further collisions and particle accumulation. ^[2] At a coarse-grained level, a particle's effective self-propulsion velocity decreases with increased density, which promotes clustering. In the more general context of self-propelled particle models, this behavior is known as motility-induced phase separation. ^[10] It is a type of athermal phase separation because it occurs even if the particles are spheres with hard-core (purely repulsive) interactions.

Variations

A variant of active Brownian motion involves complete directional reversals in addition to rotational diffusion. This movement pattern is seen in bacteria like Myxococcus xanthus , Pseudomonas putida, Pseudoalteromonas haloplanktis , Shewanella putrefaciens , and Pseudomonas citronellolis. ^[12]

See also

• Run-and-tumble motion  – Type of bacterial motion
• Janus particle  – Type of nanoparticle or microparticlePages displaying short descriptions of redirect targets
• Langevin equation  – Stochastic differential equation
• Active matter  – Matter behavior at system scale
• Nonequilibrium statistical mechanics  – Physics of large number of particles' statistical behaviorPages displaying short descriptions of redirect targets

Notes

1. Howse, Jonathan R.; Jones, Richard A. L.; Ryan, Anthony J.; Gough, Tim; Vafabakhsh, Reza; Golestanian, Ramin (2007-07-27). "Self-Motile Colloidal Particles: From Directed Propulsion to Random Walk". Physical Review Letters. 99 (4): 048102. doi:10.1103/PhysRevLett.99.048102.
2. Marchetti et al. 2016.
3. Zöttl & Stark 2016.
4. Peruani 2016.
5. Bechinger et al. 2016.
6. Romanczuk et al. 2012.
7. Shaebani et al. 2020.
8. Ni, Cohen Stuart & Bolhuis 2015.
9. Baek et al. 2018.
10. Cates & Tailleur 2015.
11. Fodor & Cristina Marchetti 2018.
12. Santra, Basu & Sabhapandit 2021.

Sources

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• Bechinger, Clemens; Di Leonardo, Roberto; Löwen, Hartmut; Reichhardt, Charles; Volpe, Giorgio; Volpe, Giovanni (2016-11-23). "Active Particles in Complex and Crowded Environments". Reviews of Modern Physics. 88 (4). American Physical Society (APS). doi:10.1103/revmodphys.88.045006. hdl: 11693/36533 . ISSN   0034-6861. S2CID   14940249.
• Cates, Michael E.; Tailleur, Julien (2015-03-01). "Motility-Induced Phase Separation". Annual Review of Condensed Matter Physics. 6 (1). Annual Reviews: 219–244. arXiv: 1406.3533 . doi:10.1146/annurev-conmatphys-031214-014710. ISSN   1947-5454. S2CID   15672131.
• Fodor, Étienne; Cristina Marchetti, M. (2018). "The statistical physics of active matter: From self-catalytic colloids to living cells". Physica A: Statistical Mechanics and Its Applications. 504. Elsevier BV: 106–120. arXiv: 1708.08652 . doi:10.1016/j.physa.2017.12.137. ISSN   0378-4371. S2CID   119450187.
• Howse, Jonathan R.; Jones, Richard A. L.; Ryan, Anthony J.; Gough, Tim; Vafabakhsh, Reza; Golestanian, Ramin (2007-07-27). "Self-Motile Colloidal Particles: From Directed Propulsion to Random Walk". Physical Review Letters. 99 (4): 048102. doi:10.1103/PhysRevLett.99.048102.
• Marchetti, M. Cristina; Fily, Yaouen; Henkes, Silke; Patch, Adam; Yllanes, David (2016). "Minimal model of active colloids highlights the role of mechanical interactions in controlling the emergent behavior of active matter". Current Opinion in Colloid & Interface Science. 21. Elsevier BV: 34–43. arXiv: 1510.00425 . doi:10.1016/j.cocis.2016.01.003. ISSN   1359-0294. S2CID   97138568.
• Ni, Ran; Cohen Stuart, Martien A.; Bolhuis, Peter G. (2015-01-07). "Tunable Long Range Forces Mediated by Self-Propelled Colloidal Hard Spheres". Physical Review Letters. 114 (1). American Physical Society (APS): 018302. arXiv: 1403.1533 . doi:10.1103/physrevlett.114.018302. ISSN   0031-9007. PMID   25615510. S2CID   8776685.
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