Large-scale collective properties of self-propelled rods

Diffusion properties of self-propelled particles in cellular flows

We study the dynamics of a self-propelled particle advected by a steady laminar flow. The persistent motion of the self-propelled particle is described by an active Ornstein-Uhlenbeck process. We focus on the diffusivity properties of the particle as a function of persistence time and free-diffusion coefficient, revealing non-monotonic behaviors, with the occurrence of a minimum and a steep growth in the regime of large persistence time. In the latter limit, we obtain an analytical prediction for the scaling of the diffusion coefficient with the parameters of the active force. Our study sheds light on the effect of a flow-field on the diffusion of active particles, such as living microorganisms and motile phytoplankton in fluids.

Effect of particle fraction on phase transitions in an active-passive particles system

We study phase transition in a binary system of monodisperse active and passive particles. The particles are initially randomly positioned inside a fixed boundary square enclosure. The active particles can move with their self-propulsion force. Whereas, the passive particles do not have any self-propulsion force, and they move by the spatial interactions with other particles. An alignment force in our discrete element model causes the emergence of collective milling motion. Without this alignment interaction, the particle system remains in a disordered phase. Whereas, the ordered milling phase is attained after achieving a minimum coordination among neighboring particles. The phase transition from disordered to ordered depends upon the relative effect of self-propulsion and the alignment, initial states of the particles, noise level, and the fraction of the active particles present in the system. The phase transition we observed is of first-order nature.

Rectification and separation of mixtures of active and passive particles driven by temperature difference

Transport and separation of binary mixtures of active and passive particles are investigated in the presence of temperature differences. It is found that temperature differences can strongly affect the rectification and separation of the mixtures. For active particles, there exists an optimal temperature difference at which the rectified efficiency is maximal. Passive particles are not propelled and move by collisions with active particles, so the response to temperature differences is more complicated. By changing the system parameters, active particles can change their directions, while passive particles always move in the same direction. The simulation results show that the separation of mixtures is sensitive to the system parameters, such as the angular velocity, the temperature difference, and the polar alignment. The mixed particles can be completely separated under certain conditions.

The 2020 motile active matter roadmap

Activity and autonomous motion are fundamental in living and engineering systems. This has stimulated the new field of 'active matter' in recent years, which focuses on the physical aspects of propulsion mechanisms, and on motility-induced emergent collective behavior of a larger number of identical agents. The scale of agents ranges from nanomotors and microswimmers, to cells, fish, birds, and people. Inspired by biological microswimmers, various designs of autonomous synthetic nano- and micromachines have been proposed. Such machines provide the basis for multifunctional, highly responsive, intelligent (artificial) active materials, which exhibit emergent behavior and the ability to perform tasks in response to external stimuli. A major challenge for understanding and designing active matter is their inherent nonequilibrium nature due to persistent energy consumption, which invalidates equilibrium concepts such as free energy, detailed balance, and time-reversal symmetry. Unraveling, predicting, and controlling the behavior of active matter is a truly interdisciplinary endeavor at the interface of biology, chemistry, ecology, engineering, mathematics, and physics. The vast complexity of phenomena and mechanisms involved in the self-organization and dynamics of motile active matter comprises a major challenge. Hence, to advance, and eventually reach a comprehensive understanding, this important research area requires a concerted, synergetic approach of the various disciplines. The 2020 motile active matter roadmap of Journal of Physics: Condensed Matter addresses the current state of the art of the field and provides guidance for both students as well as established scientists in their efforts to advance this fascinating area.

Polar pattern formation induced by contact following locomotion in a multicellular system

Biophysical mechanisms underlying collective cell migration of eukaryotic cells have been studied extensively in recent years. One mechanism that induces cells to correlate their motions is contact inhibition of locomotion, by which cells migrating away from the contact site. Here, we report that tail-following behavior at the contact site, termed contact following locomotion (CFL), can induce a non-trivial collective behavior in migrating cells. We show the emergence of a traveling band showing polar order in a mutant Dictyostelium cell that lacks chemotactic activity. We find that CFL is the cell-cell interaction underlying this phenomenon, enabling a theoretical description of how this traveling band forms. We further show that the polar order phase consists of subpopulations that exhibit characteristic transversal motions with respect to the direction of band propagation. These findings describe a novel mechanism of collective cell migration involving cell-cell interactions capable of inducing traveling band with polar order.

From scalar to polar active matter: Connecting simulations with mean-field theory

We study numerically the phase behavior of self-propelled elliptical particles interacting through the "hard" repulsive Gay-Berne potential at infinite Péclet number. Changing a single parameter, the aspect ratio, allows us to continuously go from discoid active Brownian particles to elongated polar rods. Discoids show phase separation, which changes to a cluster state of polar domains, which then form polar bands as the aspect ratio is increased. From the simulations, we identify and extract the two effective parameters entering the mean-field description: the force imbalance coefficient and the effective coupling to the local polarization. These two coefficients are sufficient to obtain a complete and consistent picture, unifying the paradigms of scalar and polar active matter.

Gliding filament system giving both global orientational order and clusters in collective motion

Emergence and collapse of coherent motions of self-propelled particles are affected more by particle motions and interactions than by their material or biological details. In the reconstructed systems of biofilaments and molecular motors, several types of collective motion including a global-order pattern emerge due to the alignment interaction. Meanwhile, earlier studies show that the alignment interaction of a binary collision of biofilaments is too weak to form the global order. The multiple collision is revealed to be important to achieve global order, but it is still unclear what kind of multifilament collision is actually involved. In this study, we demonstrate that not only alignment but also crossing of two filaments is essential to produce an effective multiple-particle interaction and the global order. We design the reconstructed system of biofilaments and molecular motors to vary a probability of the crossing of biofilaments on a collision and thus control the effect of volume exclusion. In this system, biofilaments glide along their polar strands on the turf of molecular motors and can align themselves nematically when they collide with each other. Our experiments show the counterintuitive result, in which the global order is achieved only when the crossing is allowed. When the crossing is prohibited, the cluster pattern emerges instead. We also investigate the numerical model in which we can change the strength of the volume exclusion effect and find that the global orientational order and clusters emerge with weak and strong volume exclusion effects, respectively. With those results and simple theory, we conclude that not only alignment but also finite crossing probability are necessary for the effective multiple-particles interaction forming the global order. Additionally, we describe the chiral symmetry breaking of a microtubule motion which causes a rotation of global alignment.

Spontaneous Velocity Alignment in Motility-Induced Phase Separation

We study a system of purely repulsive spherical self-propelled particles in the minimal setup inducing motility-induced phase separation (MIPS). We show that, even if explicit alignment interactions are absent, a growing order in the velocities of the clustered particles accompanies MIPS. Particles arrange into aligned or vortexlike domains whose size increases as the persistence of the self-propulsion grows, an effect that is quantified studying the spatial correlation function of the velocities. We explain the velocity alignment by unveiling a hidden alignment interaction of the Vicsek-like form, induced by the interplay between steric interactions and self-propulsion.

Extracellular matrix anisotropy is determined by TFAP2C-dependent regulation of cell collisions

The isotropic or anisotropic organization of biological extracellular matrices has important consequences for tissue function. We study emergent anisotropy using fibroblasts that generate varying degrees of matrix alignment from uniform starting conditions. This reveals that the early migratory paths of fibroblasts are correlated with subsequent matrix organization. Combined experimentation and adaptation of Vicsek modelling demonstrates that the reorientation of cells relative to each other following collision plays a role in generating matrix anisotropy. We term this behaviour 'cell collision guidance'. The transcription factor TFAP2C regulates cell collision guidance in part by controlling the expression of RND3. RND3 localizes to cell-cell collision zones where it downregulates actomyosin activity. Cell collision guidance fails without this mechanism in place, leading to isotropic matrix generation. The cross-referencing of alignment and TFAP2C gene expression signatures against existing datasets enables the identification and validation of several classes of pharmacological agents that disrupt matrix anisotropy.

Understanding Dense Active Nematics from Microscopic Models

We study dry, dense active nematics at both particle and continuous levels. Specifically, extending the Boltzmann-Ginzburg-Landau approach, we derive well-behaved hydrodynamic equations from a Vicsek-style model with nematic alignment and pairwise repulsion. An extensive study of the phase diagram shows qualitative agreement between the two levels of description. We find in particular that the dynamics of topological defects strongly depends on parameters and can lead to "arch" solutions forming a globally polar, smecticlike arrangement of Néel walls. We show how these configurations are at the origin of the defect ordered states reported previously. This work offers a detailed understanding of the theoretical description of dense active nematics directly rooted in their microscopic dynamics.

Chemotactic behaviour of Escherichia coli at high cell density

At high cell density, swimming bacteria exhibit collective motility patterns, self-organized through physical interactions of a however still debated nature. Although high-density behaviours are frequent in natural situations, it remained unknown how collective motion affects chemotaxis, the main physiological function of motility, which enables bacteria to follow environmental gradients in their habitats. Here, we systematically investigate this question in the model organism Escherichia coli, varying cell density, cell length, and suspension confinement. The characteristics of the collective motion indicate that hydrodynamic interactions between swimmers made the primary contribution to its emergence. We observe that the chemotactic drift is moderately enhanced at intermediate cell densities, peaks, and is then strongly suppressed at higher densities. Numerical simulations reveal that this suppression occurs because the collective motion disturbs the choreography necessary for chemotactic sensing. We suggest that this physical hindrance imposes a fundamental constraint on high-density behaviours of motile bacteria, including swarming and the formation of multicellular aggregates and biofilms.

Quantitative Assessment of the Toner and Tu Theory of Polar Flocks

We present a quantitative assessment of the Toner and Tu theory describing the universal scaling of fluctuations in polar phases of dry active matter. Using large-scale simulations of the Vicsek model in two and three dimensions, we find the overall phenomenology and generic algebraic scaling predicted by Toner and Tu, but our data on density correlations reveal some qualitative discrepancies. The values of the associated scaling exponents we estimate differ significantly from those conjectured in 1995. In particular, we identify a large crossover scale beyond which flocks are only weakly anisotropic. We discuss the meaning and consequences of these results.

Re-entrant phase separation in nematically aligning active polar particles

We present a numerical study of the phase behavior of repulsively interacting active polar particles that align their active velocities nematically. The amplitude of the active velocity, and the noise in its orientational alignment control the active nature of the system. At high values of orientational noise, the structural fluid undergoes a continuous nematic-isotropic transition in active orientation. This transition is well separated from an active phase separation, characterized by the formation of high density hexatic clusters, observed at lower noise strengths. With increasing activity, the system undergoes a re-entrant fluid - phase separation - fluid transition. The phase coexistence at low activity can be understood in terms of motility induced phase separation. In contrast, the re-melting of hexatic clusters, and the collective motion at low orientational noise are dominated by flocking behavior. At high activity, sliding and jamming of polar sub-clusters, formation of grain boundaries, lane formation, and subsequent fragmentation of the polar patches mediate remelting.

Controlling the structure and mixing properties of anisotropic active particles with the direction of self-propulsion

In the search for advanced materials active particles could offer unique structural and functional properties, with tunable time-dependent characteristics. We demonstrate here that the direction of self-propulsion, relative to the particle orientation, may be as influential for the phase behavior as the pair interactions are for passive particles, and enable dynamic properties that are not available to passive systems. We perform simulations on ensembles of self-propelled squares, and find that squares that self-propel in the direction perpendicular to a side rapidly reach a steady state with a characteristic cluster distribution, positional order, and well-defined diffusion constant. After tuning the direction towards a corner, the particles form large and dense clusters that show a transient collective motion, and display remarkable fluctuations over long time scales, with a distinct periodicity. Clusters of these particles appear unstable beyond a critical size, and susceptible to a catastrophic disintegration. Directionality is found to effect equally sharp transitions in the mixing properties of active squares and passive squares, and the behavior of the passive ensemble. We relate directionality to the collision dynamics and the resulting reaction network of clusters, evolved by a Kinetic Monte Carlo algorithm, to correlate propulsion direction to the observed phase behavior. Understanding this behavior could offer new design rules for programmable materials, and grant further insights in the dynamic processes that nature employs for self-assembly.

Matrix feedback enables diverse higher-order patterning of the extracellular matrix

The higher-order patterning of extra-cellular matrix in normal and pathological tissues has profound consequences on tissue function. Whilst studies have documented both how fibroblasts create and maintain individual matrix fibers and how cell migration is altered by the fibers they interact with, a model unifying these two aspects of tissue organization is lacking. Here we use computational modelling to understand the effect of this interconnectivity between fibroblasts and matrix at the mesoscale level. We created a unique adaptation to the Vicsek flocking model to include feedback from a second layer representing the matrix, and use experimentation to parameterize our model and validate model-driven hypotheses. Our two-layer model demonstrates that feedback between fibroblasts and matrix increases matrix diversity creating higher-order patterns. The model can quantitatively recapitulate matrix patterns of tissues in vivo. Cells follow matrix fibers irrespective of when the matrix fibers were deposited, resulting in feedback with the matrix acting as temporal 'memory' to collective behaviour, which creates diversity in topology. We also establish conditions under which matrix can be remodelled from one pattern to another. Our model elucidates how simple rules defining fibroblast-matrix interactions are sufficient to generate complex tissue patterns.

Avalanche Interpretation of the Power-Law Energy Spectrum in Three-Dimensional Dense Granular Flow

Turbulence is ubiquitous in nonequilibrium systems, and it has been noted that even dense granular flows exhibit characteristics that are typical of turbulent flow, such as the power-law energy spectrum. However, studies on the turbulentlike behavior of granular flows are limited to two-dimensional (2D) flow. We demonstrate that the statistics in three-dimensional (3D) flow are qualitatively different from those in 2D flow. We also elucidate that avalanche dynamics can explain this dimensionality dependence. Moreover, we define clusters of collectively moving particles that are equivalent to vortex filaments. The clusters unveil complicated structures in 3D flows that are absent in 2D flows.

Self-organization of swimmers drives long-range fluid transport in bacterial colonies

Motile subpopulations in microbial communities are believed to be important for dispersal, quest for food, and material transport. Here, we show that motile cells in sessile colonies of peritrichously flagellated bacteria can self-organize into two adjacent, centimeter-scale motile rings surrounding the entire colony. The motile rings arise from spontaneous segregation of a homogeneous swimmer suspension that mimics a phase separation; the process is mediated by intercellular interactions and shear-induced depletion. As a result of this self-organization, cells drive fluid flows that circulate around the colony at a constant peak speed of ~30 µm s⁻¹, providing a stable and high-speed avenue for directed material transport at the macroscopic scale. Our findings present a unique form of bacterial self-organization that influences population structure and material distribution in colonies.

Motile and non-motile subpopulations often coexist in bacterial communities. Here, Xu et al. show that motile cells in colonies of common flagellated bacteria can self-organize into two adjacent motile rings, driving stable flows of fluid and materials around the colony.

Flow and clogging of particles in shaking random obstacles

Transport of three types of particles (passive particles, active particles, and polar particles) is investigated in a random obstacle array in the presence of a dc drift force. The obstacles are static or synchronously shake along the given direction. When the obstacles are static, the average velocity is a peaked function of the dc drift force (negative differential mobility) for low particle density, while the average velocity monotonically increases with the dc drift force (positive differential mobility) for high particle density. Under the same conditions, passive particles are most likely to pass through the obstacles, while polar particles are easily trapped by the obstacles. The polar alignment can strongly reduce the overall mobility of particles. When the obstacles shake along the given direction, the optimal shaking frequency or amplitude can maximize the average velocity. It is more effective to reduce clogging for the transverse shaking than that for the longitudinal shaking.

Collective oscillation in dense suspension of self-propelled chiral rods

Active particles capable of self-propulsion commonly exhibit rich collective dynamics and have attracted increasing attention due to their applications in biology, robotics, social transport, and biomedicine. However, it remains unclear how the geometric features of active particles affect their collective behaviors. In this paper, we explore the collective dynamics of L-shaped active rods. We show that a dense suspension of self-propelled L-shaped rods exhibits fascinating non-equilibrium oscillatory dynamic clustering. A new oscillation phase can form due to distinct collisions and aggregation mechanisms arising from the L-shaped chirality of elements. A generic diagram of emerging states is provided over a wide range of geometric parameters. Our findings show that the comparative strength between the periodic separation and proximity effect from chirality and the alignment effect from elongated geometry drive the formation and transition of dynamic patterns. This chirality-triggered oscillation phase suggests a new route to understand active matter and paves a way for emerging applications.

Activity-induced mixing and phase transitions of self-propelled swimmers

We study the mixing of active swimmers. Two different types of swimmers (modeled as particles) are placed initially in two boxes with an interconnection between them. The mixing of swimmers happens as they move with their own self-propelled forces. The self-propelled force is constant and the direction of the exerted thrust is governed by the neighboring swimmers. Overall mixing of the swimmers depends on the magnitude of the exerted thrust, the initial packing fraction, and the activity level. Different nonequilibrium states are also identified depending on the exerted thrust and the initial packing fraction of the swimmers.

How antagonistic salts cause nematic ordering and behave like diblock copolymers

We present simulation results and an explanatory theory on how antagonistic salts affect the spinodal decomposition of binary fluid mixtures. We find that spinodal decomposition is arrested and complex structures form only when electrostatic ion-ion interactions are small. In this case, the fluid and ion concentrations couple and the charge field can be approximated as a polynomial function of the relative fluid concentrations alone. When the solvation energy associated with transferring an ion from one fluid phase to the other is of the order of a few k_BT, the coupled fluid and charge fields evolve according to the Ohta-Kawasaki free energy functional. This allows us to accurately predict structure sizes and reduce the parameter space to two dimensionless numbers. The lamellar structures induced by the presence of the antagonistic salt in our simulations exhibit a high degree of nematic ordering and the growth of ordered domains over time follows a power law. This power law carries a time exponent proportional to the salt concentration. We qualitatively reproduce and interpret neutron scattering data from previous experiments of similar systems. The dissolution of structures at high salt concentrations observed in these experiments agrees with our simulations, and we explain it as the result of a vanishing surface tension due to electrostatic contributions. We conclude by presenting 3D results showing the same morphologies as predicted by the Ohta-Kawasaki model as a function of volume fraction and suggesting that our findings from 2D systems remain valid in 3D.

Reaction processes among self-propelled particles

We study a system of self-propelled disks that perform run-and-tumble motion, where particles can adopt more than one internal state. One of those internal states can be transmitted to other particle if the particle carrying this state maintains physical contact with another particle for a finite period of time. We refer to this process as a reaction process and to the different internal states as particle species, making an analogy to chemical reactions. The studied system may fall into an absorbing phase, where due to the disappearance of one of the particle species no further reaction can occur, or may remain in an active phase where particles constantly react. By combining individual-based simulations and mean-field arguments, we study the dependency of the equilibrium densities of particle species on motility parameters, specifically the active speed v₀ and tumbling frequency λ. We find that the equilibrium densities of particle species exhibit two very distinct, non-trivial scaling regimes, with v₀ and λ depending on whether the system is in the so-called ballistic or diffusive regime. Our mean-field estimates lead to an effective renormalization of reaction rates that allow building the phase-diagram v₀-λ that separates the absorbing and active phases. We find an excellent agreement between numerical simulations and mean-field estimates. This study is a necessary step towards an understanding of phase transitions into absorbing states in active systems and sheds light on the spreading of information/signaling among moving elements.

Learning the space-time phase diagram of bacterial swarm expansion

Most living systems, from individual cells to tissues and swarms, display collective self-organization on length scales that are much larger than those of the individual units that drive this organization. A fundamental challenge is to understand how properties of microscopic components determine macroscopic, multicellular biological function. Our study connects intracellular physiology to macroscale collective behaviors during multicellular development, spanning five orders of magnitude in length and six orders of magnitude in time, using bacterial swarming as a model system. This work is enabled by a high-throughput adaptive microscopy technique, which we combined with genetics, machine learning, and mathematical modeling to reveal the phase diagram of bacterial swarming and that cell–cell interactions within each swarming phase are dominated by mechanical interactions.

Coordinated dynamics of individual components in active matter are an essential aspect of life on all scales. Establishing a comprehensive, causal connection between intracellular, intercellular, and macroscopic behaviors has remained a major challenge due to limitations in data acquisition and analysis techniques suitable for multiscale dynamics. Here, we combine a high-throughput adaptive microscopy approach with machine learning, to identify key biological and physical mechanisms that determine distinct microscopic and macroscopic collective behavior phases which develop as Bacillus subtilis swarms expand over five orders of magnitude in space. Our experiments, continuum modeling, and particle-based simulations reveal that macroscopic swarm expansion is primarily driven by cellular growth kinetics, whereas the microscopic swarming motility phases are dominated by physical cell–cell interactions. These results provide a unified understanding of bacterial multiscale behavioral complexity in swarms.

A statistical physics view of swarming bacteria

Bacterial swarming is a collective mode of motion in which cells migrate rapidly over surfaces, forming dynamic patterns of whirls and jets. This review presents a physical point of view of swarming bacteria, with an emphasis on the statistical properties of the swarm dynamics as observed in experiments. The basic physical principles underlying the swarm and their relation to contemporary theories of collective motion and active matter are reviewed and discussed in the context of the biological properties of swarming cells. We suggest a paradigm according to which bacteria have optimized some of their physical properties as a strategy for rapid surface translocation. In other words, cells take advantage of favorable physics, enabling efficient expansion that enhances survival under harsh conditions.

The interplay between activity and filament flexibility determines the emergent properties of active nematics

Active nematics are microscopically driven liquid crystals that exhibit dynamical steady states characterized by the creation and annihilation of topological defects. Motivated by differences between previous simulations of active nematics based on rigid rods and experimental realizations based on semiflexible biopolymer filaments, we describe a large-scale simulation study of a particle-based computational model that explicitly incorporates filament semiflexibility. We find that energy injected into the system at the particle scale preferentially excites bend deformations, reducing the apparent filament bend modulus. The emergent characteristics of the active nematic depend on activity and flexibility only through this activity-renormalized bend 'modulus', demonstrating that apparent values of material parameters, such as the Frank 'constants', depend on activity. Thus, phenomenological parameters within continuum hydrodynamic descriptions of active nematics must account for this dependence. Further, we present a systematic way to estimate these parameters from observations of deformation fields and defect shapes in experimental or simulation data.

Traveling pulse emerges from coupled intermittent walks: A case study in sheep

Monitoring small groups of sheep in spontaneous evolution in the field, we decipher behavioural rules that sheep follow at the individual scale in order to sustain collective motion. Individuals alternate grazing mode at null speed and moving mode at walking speed, so cohesive motion stems from synchronising when they decide to switch between the two modes. We propose a model for the individual decision making process, based on switching rates between stopped / walking states that depend on behind / ahead locations and states of the others. We parametrize this model from data. Next, we translate this (microscopic) individual-based model into its density-flow (macroscopic) equations counterpart. Numerical solving these equations display a traveling pulse propagating at constant speed even though each individual is at any moment either stopped or walking. Considering the minimal model embedded in these equations, we derive analytically the steady shape of the pulse (sech square). The parameters of the pulse (shape and speed) are expressed as functions of individual parameters. This pulse emerges from the non linear coupling of start/stop individual decisions which compensate exactly for diffusion and promotes a steady ratio of walking / stopped individuals, which in turn determines the traveling speed of the pulse. The system seems to converge to this pulse from any initial condition, and to recover the pulse after perturbation. This gives a high robustness to this coordination mechanism.

Transport of particles driven by the traveling obstacle arrays

Transport of three types of particles (passive particles, active particles without polar interaction, and active particles with polar interaction) is numerically investigated in the presence of traveling obstacle arrays. The transport behaviors are different for different types of particles. For passive particles, there exists an optimal traveling speed (or the translational diffusion) at which the average velocity of particles takes its maximum value. For active particles without polar interaction, the average velocity of particles is a peaked function of the obstacle traveling speed. The average velocity decreases monotonically with increase of the rotational diffusion for large driving speed, while it is a peaked function of the rotational diffusion for small driving speed. For active particles with polar interaction, interestingly, within particular parameter regimes, active particles can move in the opposite direction to the obstacles. The average velocity of particles can change its direction by changing the system parameters (the obstacles driving speed, the polar interaction strength, and the rotational diffusion).

Active dumbbells: Dynamics and morphology in the coexisting region

With the help of molecular dynamics simulations we study an ensemble of active dumbbells in purely repulsive interaction. We derive the phase diagram in the density-activity plane and we characterise the various phases with liquid, hexatic and solid character. The analysis of the structural and dynamical properties, such as enstrophy, mean-square displacement, polarisation, and correlation functions, shows the continuous character of liquid and hexatic phases in the coexisting region when the activity is increased starting from the passive limit.

Scale invariance in natural and artificial collective systems: a review

Self-organized collective coordinated behaviour is an impressive phenomenon, observed in a variety of natural and artificial systems, in which coherent global structures or dynamics emerge from local interactions between individual parts. If the degree of collective integration of a system does not depend on size, its level of robustness and adaptivity is typically increased and we refer to it as scale-invariant. In this review, we first identify three main types of self-organized scale-invariant systems: scale-invariant spatial structures, scale-invariant topologies and scale-invariant dynamics. We then provide examples of scale invariance from different domains in science, describe their origins and main features and discuss potential challenges and approaches for designing and engineering artificial systems with scale-invariant properties.

A continuous-time persistent random walk model for flocking

A classical random walker is characterized by a random position and velocity. This sort of random walk was originally proposed by Einstein to model Brownian motion and to demonstrate the existence of atoms and molecules. Such a walker represents an inanimate particle driven by environmental fluctuations. On the other hand, there are many examples of so-called "persistent random walkers," including self-propelled particles that are able to move with almost constant speed while randomly changing their direction of motion. Examples include living entities (ranging from flagellated unicellular organisms to complex animals such as birds and fish), as well as synthetic materials. Here we discuss such persistent non-interacting random walkers as a model for active particles. We also present a model that includes interactions among particles, leading to a transition to flocking, that is, to a net flux where the majority of the particles move in the same direction. Moreover, the model exhibits secondary transitions that lead to clustering and more complex spatially structured states of flocking. We analyze all these transitions in terms of bifurcations using a number of mean field strategies (all to all interaction and advection-reaction equations for the spatially structured states), and compare these results with direct numerical simulations of ensembles of these interacting active particles.

Isotropic-nematic transition of self-propelled rods in three dimensions

Using overdamped Brownian dynamics simulations we investigate the isotropic-nematic (IN) transition of self-propelled rods in three spatial dimensions. For two well-known model systems (Gay-Berne potential and hard spherocylinders) we find that turning on activity moves to higher densities the phase boundary separating an isotropic phase from a (nonpolar) nematic phase. This active IN phase boundary is distinct from the boundary between isotropic and polar-cluster states previously reported in two-dimensional simulation studies and, unlike the latter, is not sensitive to the system size. We thus identify a generic feature of anisotropic active particles in three dimensions.

Emergence of coexisting ordered states in active matter systems

Active systems can produce a far greater variety of ordered patterns than conventional equilibrium systems. In particular, transitions between disorder and either polar- or nematically ordered phases have been predicted and observed in two-dimensional active systems. However, coexistence between phases of different types of order has not been reported. We demonstrate the emergence of dynamic coexistence of ordered states with fluctuating nematic and polar symmetry in an actomyosin motility assay. Combining experiments with agent-based simulations, we identify sufficiently weak interactions that lack a clear alignment symmetry as a prerequisite for coexistence. Thus, the symmetry of macroscopic order becomes an emergent and dynamic property of the active system. These results provide a pathway by which living systems can express different types of order by using identical building blocks.

Self-Propelled Particles with Velocity Reversals and Ferromagnetic Alignment: Active Matter Class with Second-Order Transition to Quasi-Long-Range Polar Order

We introduce and study in two dimensions a new class of dry, aligning active matter that exhibits a direct transition to orientational order, without the phase-separation phenomenology usually observed in this context. Characterized by self-propelled particles with velocity reversals and a ferromagnetic alignment of polarities, systems in this class display quasi-long-range polar order with continuously varying scaling exponents, yet a numerical study of the transition leads to conclude that it does not belong to the Berezinskii-Kosterlitz-Thouless universality class but is best described as a standard critical point with an algebraic divergence of correlations. We rationalize these findings by showing that the interplay between order and density changes the role of defects.

Collective dynamics of self-propelled semiflexible filaments

The collective behavior of active semiflexible filaments is studied with a model of tangentially driven self-propelled worm-like chains. The combination of excluded-volume interactions and self-propulsion leads to several distinct dynamic phases as a function of bending rigidity, activity, and aspect ratio of individual filaments. We consider first the case of intermediate filament density. For high-aspect-ratio filaments, we identify a transition with increasing propulsion from a state of free-swimming filaments to a state of spiraled filaments with nearly frozen translational motion. For lower aspect ratios, this gas-of-spirals phase is suppressed with growing density due to filament collisions; instead, filaments form clusters similar to self-propelled rods. As activity increases, finite bending rigidity strongly effects the dynamics and phase behavior. Flexible filaments form small and transient clusters, while stiffer filaments organize into giant clusters, similarly to self-propelled rods, but with a reentrant phase behavior from giant to smaller clusters as activity becomes large enough to bend the filaments. For high filament densities, we identify a nearly frozen jamming state at low activities, a nematic laning state at intermediate activities, and an active-turbulence state at high activities. The latter state is characterized by a power-law decay of the energy spectrum as a function of wave number. The resulting phase diagrams encapsulate tunable non-equilibrium steady states that can be used in the organization of living matter.

Spatial flocking: Control by speed, distance, noise and delay

Fish, birds, insects and robots frequently swim or fly in groups. During their three dimensional collective motion, these agents do not stop, they avoid collisions by strong short-range repulsion, and achieve group cohesion by weak long-range attraction. In a minimal model that is isotropic, and continuous in both space and time, we demonstrate that (i) adjusting speed to a preferred value, combined with (ii) radial repulsion and an (iii) effective long-range attraction are sufficient for the stable ordering of autonomously moving agents in space. Our results imply that beyond these three rules ordering in space requires no further rules, for example, explicit velocity alignment, anisotropy of the interactions or the frequent reversal of the direction of motion, friction, elastic interactions, sticky surfaces, a viscous medium, or vertical separation that prefers interactions within horizontal layers. Noise and delays are inherent to the communication and decisions of all moving agents. Thus, next we investigate their effects on ordering in the model. First, we find that the amount of noise necessary for preventing the ordering of agents is not sufficient for destroying order. In other words, for realistic noise amplitudes the transition between order and disorder is rapid. Second, we demonstrate that ordering is more sensitive to displacements caused by delayed interactions than to uncorrelated noise (random errors). Third, we find that with changing interaction delays the ordered state disappears at roughly the same rate, whereas it emerges with different rates. In summary, we find that the model discussed here is simple enough to allow a fair understanding of the modeled phenomena, yet sufficiently detailed for the description and management of large flocks with noisy and delayed interactions. Our code is available at http://github.com/fij/floc.

Large-scale chirality in an active layer of microtubules and kinesin motor proteins

During the early developmental process of organisms, the formation of left-right laterality requires a subtle mechanism, as it is associated with other principal body axes. Any inherent chiral feature in an egg cell can in principal trigger this spontaneous breaking of chiral symmetry. Individual microtubules, major cytoskeletal filaments, are known as chiral objects. However, to date there lacks convincing evidence of a hierarchical connection of the molecular nature of microtubules to large-scale chirality, particularly at the length scale of an entire cell. Here we assemble an in vitro active layer, consisting of microtubules and kinesin motor proteins, on a glass surface. Upon inclusion of methyl cellulose, the layered system exhibits a long-range active nematic phase, characterized by the global alignment of gliding MTs. This nematic order spans over the entire system size in the millimeter range and, remarkably, allows hidden collective chirality to emerge as counterclockwise global rotation of the active MT layer. The analysis based on our theoretical model suggests that the emerging global nematic order results from the local alignment of MTs, stabilized by methyl cellulose. It also suggests that the global rotation arises from the MTs' intrinsic curvature, leading to preferential handedness. Given its flexibility, this layered in vitro cytoskeletal system enables the study of membranous protein behavior responsible for important cellular developmental processes.

Collective motion of rod-shaped self-propelled particles through collision

Self-propelled rods, which propel by themselves in the direction from the tail to the head and align nematically through collision, have been well-investigated theoretically. Various phenomena including true long-range ordered phase with the Giant number fluctuations, and the collective motion composed of many vorices were predicted using the minimal mathematical models of self-propelled rods. Using filamentous bacteria and running microtubules, we found that the predicted phenomena by the minimal models occur in the real world. This strongly indicates that there exists the unified description of self-propelled rods independent of the details of the systems. The theoretically predicted phenomena and the experimental results concerning the phenomena are reviewed.

Derivation of a hydrodynamic theory for mesoscale dynamics in microswimmer suspensions

In this paper, we systematically derive a fourth-order continuum theory capable of reproducing mesoscale turbulence in a three-dimensional suspension of microswimmers. We start from overdamped Langevin equations for a generic microscopic model (pushers or pullers), which include hydrodynamic interactions on both small length scales (polar alignment of neighboring swimmers) and large length scales, where the solvent flow interacts with the order parameter field. The flow field is determined via the Stokes equation supplemented by an ansatz for the stress tensor. In addition to hydrodynamic interactions, we allow for nematic pair interactions stemming from excluded-volume effects. The results here substantially extend and generalize earlier findings [S. Heidenreich et al., Phys. Rev. E 94, 020601 (2016)2470-004510.1103/PhysRevE.94.020601], in which we derived a two-dimensional hydrodynamic theory. From the corresponding mean-field Fokker-Planck equation combined with a self-consistent closure scheme, we derive nonlinear field equations for the polar and the nematic order parameter, involving gradient terms of up to fourth order. We find that the effective microswimmer dynamics depends on the coupling between solvent flow and orientational order. For very weak coupling corresponding to a high viscosity of the suspension, the dynamics of mesoscale turbulence can be described by a simplified model containing only an effective microswimmer velocity.

Self-assembly of rigid magnetic rods consisting of single dipolar beads in two dimensions

Molecular dynamics simulations are used to investigate the structural properties of a two-dimensional ensemble of magnetic rods, which are modeled as aligned single dipolar beads. The obtained self-assembled configurations can be characterized as (1) clusters, (2) percolated, and (3) ordered structures, and their structural properties are investigated in detail. By increasing the aspect ratio of the magnetic rods, we show that the percolation transition is suppressed due to the reduced mobility of the rods in two dimensions. Such a behavior is opposite to the one observed in three dimensions. A magnetic bulk phase is found with local ferromagnetic order and an unusual nonmonotonic behavior of the nematic order is observed.

Low-noise phase of a two-dimensional active nematic system

We consider a collection of self-driven apolar particles on a substrate that organize into an active nematic phase at sufficiently high density or low noise. Using the dynamical renormalization group, we systematically study the two-dimensional fluctuating ordered phase in a coarse-grained hydrodynamic description involving both the nematic director and the conserved density field. In the presence of noise, we show that the system always displays only quasi-long-ranged orientational order beyond a crossover scale. A careful analysis of the nonlinearities permitted by symmetry reveals that activity is dangerously irrelevant over the linearized description, allowing giant number fluctuations to persist although now with strong finite-size effects and a nonuniversal scaling exponent. Nonlinear effects from the active currents lead to power-law correlations in the density field, thereby preventing macroscopic phase separation in the thermodynamic limit.

Self-propulsion of a grain-filled dimer in a vertically vibrated channel

Steady dissipation of energy is a crucial property that distinguishes active particles from Brownian particles. However, it is not straightforward to explicitly model the dissipative property of existing active particles driven by a vibrating plate. We present a novel active particle that can be explicitly modeled by Newtonian dynamics of a conservative force field plus two asymmetrical dissipative terms. The particle is a dimer consisting of two ping-pong balls connected by a rigid rod, and its two balls are filled with granular particles of the same total mass but of different grain size. This dimer placed on a vibrating plate exhibits 3 types of motion – by tuning the frequency and the amplitude of the vibration, the dimer undergoes either a directed motion toward the small (or large) grain-filled side or an unbiased random motion. We investigate the various modes of motion both experimentally and numerically and show that the directed motion is a result of the asymmetric damping due to the size difference in the filling grains. Furthermore, the numerical simulation reveals that the dimer’s dynamics in either directed motion mode resembles a limit cycle attractor that is independent of its initial condition.

How to desynchronize quorum-sensing networks

In this paper we investigate how so-called quorum-sensing networks can be desynchronized. Such networks, which arise in many important application fields, such as systems biology, are characterized by the fact that direct communication between network nodes is superimposed to communication with a shared, environmental variable. In particular, we provide a new sufficient condition ensuring that the trajectories of these quorum-sensing networks diverge from their synchronous evolution. Then, we apply our result to study two applications.

Transport of alignment active particles in funnel structures

We study the transport of alignment active particles in complex confined structures (an array of asymmetric funnels). It is found that due to the existence of the multiple pathways, the alignment interaction can enrich the transport behavior of active particles. In an array of asymmetric funnels, the purely nematic alignment always suppresses the rectification. However, the polar alignment does not always promote the rectification, the rectification is suppressed for large self-propulsion speed. In addition, we also found the existence of optimal parameters (the self-propulsion speed and the rotational diffusion coefficient) at which the directed velocity takes its maximal value.

Flocking ferromagnetic colloids

Assemblages of microscopic colloidal particles exhibit fascinating collective motion when energized by electric or magnetic fields. The behaviors range from coherent vortical motion to phase separation and dynamic self-assembly. Although colloidal systems are relatively simple, understanding their collective response, especially under out-of-equilibrium conditions, remains elusive. We report on the emergence of flocking and global rotation in the system of rolling ferromagnetic microparticles energized by a vertical alternating magnetic field. By combing experiments and discrete particle simulations, we have identified primary physical mechanisms, leading to the emergence of large-scale collective motion: spontaneous symmetry breaking of the clockwise/counterclockwise particle rotation, collisional alignment of particle velocities, and random particle reorientations due to shape imperfections. We have also shown that hydrodynamic interactions between the particles do not have a qualitative effect on the collective dynamics. Our findings shed light on the onset of spatial and temporal coherence in a large class of active systems, both synthetic (colloids, swarms of robots, and biopolymers) and living (suspensions of bacteria, cell colonies, and bird flocks).