Aggregation and sedimentation of active Brownian particles at constant affinity

Fischer, Andreas; Chatterjee, Arkya; Speck, Thomas

doi:10.1063/1.5081115

Cited by 19 publications

(18 citation statements)

References 54 publications

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“…The transition from a purely dilute state with no clustering to a dense state with collective motion and non-homogeneous polydomains of local nematic ordering exhibits coexistence between the dilute and dense states. Such coexistence of separated phases appears to be a hallmark of self-propelled particles in general, not limited to twitching bacilliforms nor self-propelled rods, which has been studied theoretically in terms www.nature.com/scientificreports www.nature.com/scientificreports/ of motility-induced phase separation 86,87 , in simulations of active Brownian particles 18,19,88 , in self-propelled ballistic particles 23 , kinetic Monte Carlo 89 and experimentally in systems of active spherical Janus colloids 24 . Similarly, our simulations quantify the giant number fluctuations and dynamic distributions of the coverage produced by twitching motility, which are likewise expected from active nematic systems 83,90 .…”

Section: Discussionmentioning

confidence: 99%

Collective Dynamics of Model Pili-Based Twitcher-Mode Bacilliforms

Nagel

Greenberg

Shendruk

et al. 2020

Sci Rep

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Pseudomonas aeruginosa, like many bacilliforms, are not limited only to swimming motility but rather possess many motility strategies. in particular, twitching-mode motility employs hair-like pili to transverse moist surfaces with a jittery irregular crawl. twitching motility plays a critical role in redistributing cells on surfaces prior to and during colony formation. We combine molecular dynamics and rule-based simulations to study twitching-mode motility of model bacilliforms and show that there is a critical surface coverage fraction at which collective effects arise. Our simulations demonstrate dynamic clustering of twitcher-type bacteria with polydomains of local alignment that exhibit spontaneous correlated motions, similar to rafts in many bacterial communities. Active matter possesses the potential to bridge between physics and biology. Like living systems, manufactured active systems maintain far-from-equilibrium states by autonomously drawing energy from the surroundings to fuel non-thermal processes. Furthermore, active systems exhibit many of the characteristic traits of biological materials, such as spontaneous motion, self-organization and complex spatio-temporal dynamics. Communities of model bacteria, such as Pseudomonas aeruginosa, are excellent biological examples of out-of-equilibrium systems. These relatively simple living systems serve as a biophysical study of active matter in which collectivity arising from bio-mechanical action can perform essential biological roles. Theories and simulations have approached such bacterial systems by simplifying or omitting all but the most essential, lowest-order physical traits of these microbes, as well as biological complexities. From the very first considerations of active matter, self-propulsion and local alignment were identified as the fundamental components necessary for collective dynamics to emerge from active particles 1,2. Simulations of self-propelled rods and their continuum limit of active nematics have been particularly important to the field 3-14 , as recently reviewed in ref. 15. However, the universality of behaviors exhibited by active systems is still a matter of debate 16,17 and it cannot simply be taken for granted that the collective dynamics of Vicsek boids 1 , active Brownian particles 18-20 or self-propelled rods are directly inherited by microbial motility strategies. Indeed it is known that what might appear to be higher-order details can qualitatively alter the large-scale dynamics. For example, while self-propelled rods and other active colloids commonly exhibit pronounced clustering 21 , which can be explained by motility-induced phase separation or other theoretical approaches 22-24 , swimming microbes can behave as homogeneous fluids on the scales of mesoscale active turbulence 25 , with simulations suggesting that the details of hydrodynamic interactions are essential for differentiating these large-scale swimmer properties 20,26-28. Various modes of swimming motility, including but not limited to pushing, pulling, squi...

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Section: Discussionmentioning

confidence: 99%

Collective Dynamics of Model Pili-Based Twitcher-Mode Bacilliforms

Nagel

Greenberg

Shendruk

et al. 2020

Sci Rep

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“…This effective equilibrium regime was demonstrated theoretically for sedimenting RTPs 186 , ABPs 59,64,89,100,173,203,212 and AOUPs 183 , whose sedimentation profiles have been computed theoretically and lead to Eq. ( 13) in the small τ limit.…”

Section: ∂Ementioning

confidence: 71%

Time-(ir)reversibility in active matter: from micro to macro

O'Byrne¹,

Kafri²,

Tailleur³

et al. 2021

Preprint

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Active matter encompasses systems whose individual consituents dissipate energy to exert propelling forces on their environment. This rapidly developing field harbors a dynamical phenomenology with no counterpart in passive systems. The extent to which this is rooted in the breaking of time-reversibility has recently triggered an important theoretical and experimental activity which is the focus of this review. Building on recent progress in the field, we disentangle the respective roles of the arrow of time and of the non-Boltzmann nature of steady-state fluctuations in single-and many-body active systems. We show that effective time-reversible descriptions of active systems may be found at all scales, and discuss how interactions, either between constituents or with external operators, may reveal the nonequilibrium nature of the microscopic source of energy. At a time when the engineering of active materials appears within our reach, this allows us to discuss to which extent methods stemming from equilibrium statistical mechanics may guide us in their design.

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“…Our study, in line with the recent studies of Refs. [51][52][53], is an attempt to model the active matter systems in a more realistic way. As the motility is a key ingredient of the MIPS, we expect a significant effect of the fluctuations on this phenomenon.…”

Section: Collective Behaviormentioning

confidence: 99%