Active Matter Physics Research Articles

Edge current and pairing order transition in chiral bacterial vortices

Bacterial suspensions show turbulence-like spatiotemporal dynamics and vortices moving irregularly inside the suspensions. Understanding these ordered vortices is an ongoing challenge in active matter physics, and their application to the control of autonomous material transport will provide significant development in microfluidics. Despite the extensive studies, one of the key aspects of bacterial propulsion has remained elusive: The motion of bacteria is chiral, i.e., it breaks mirror symmetry. Therefore, the mechanism of control of macroscopic active turbulence by microscopic chirality is still poorly understood. Here, we report the selective stabilization of chiral rotational direction of bacterial vortices in achiral circular microwells sealed by an oil/water interface. The intrinsic chirality of bacterial swimming near the top and bottom interfaces generates chiral collective motions of bacteria at the lateral boundary of the microwell that are opposite in directions. These edge currents grow stronger as bacterial density increases, and, within different top and bottom interfaces, their competition leads to a global rotation of the bacterial suspension in a favored direction, breaking the mirror symmetry of the system. We further demonstrate that chiral edge current favors corotational configurations of interacting vortices, enhancing their ordering. The intrinsic chirality of bacteria is a key feature of the pairing order transition from active turbulence, and the geometric rule of pairing order transition may shed light on the strategy for designing chiral active matter.

Long range correlations and slow time scales in a boundary driven granular model

We consider a velocity field with linear viscous interactions defined on a one dimensional lattice. Brownian baths with different parameters can be coupled to the boundary sites and to the bulk sites, determining different kinds of non-equilibrium steady states or free-cooling dynamics. Analytical results for spatial and temporal correlations are provided by analytical diagonalisation of the system’s equations in the infinite size limit. We demonstrate that spatial correlations are scale-free and time-scales become exceedingly long when the system is driven only at the boundaries. On the contrary, in the case a bath is coupled to the bulk sites too, an exponential correlation decay is found with a finite characteristic length. This is also true in the free cooling regime, but in this case the correlation length grows diffusively in time. We discuss the crucial role of boundary driving for long-range correlations and slow time-scales, proposing an analogy between this simplified dynamical model and dense vibro-fluidized granular materials. Several generalizations and connections with the statistical physics of active matter are also suggested.

Magnetic nanohelices swimming in an optical bowl

Magnetically driven helical nanoswimmers can impact many problems related to biology and medicine, such as intracellular manipulation, microsurgery, and drug delivery, and provide a promising platform for simulating and studying the physics of active matter. Crucial aspects of studying this powerful system pertain to their motion and dynamics under different physical conditions. In this paper, we demonstrate the confinement and controlled manipulation of magnetic nanohelices within an optical bowl formed by a defocused optical tweezer. The interaction of helical swimmers with the optical confinement was modeled and further confirmed by experiments. The results suggest that the combination of optical and magnetic forces can offer interesting avenues in the study of magnetic nanoswimmers, especially those related to micro-rheology and hydrodynamics.

Dipole-Moment Induced Phototaxis and Fuel-Free Propulsion of ZnO/Pt Janus Micromotors.

Light-driven micromotors have stimulated considerate interests due to their potentials in biomedicine, environmental remediation, or serving as the model system for non-equilibrium physics of active matter. Simultaneous control over the motion direction and speed of micro/nanomotors is crucial for their functionality but still difficult since Brownian motion always randomizes the orientations. Here, a highly efficient light-driven ZnO/Pt Janus micromotor capable of aligning itself to illumination direction and exhibiting negative phototaxis at high speeds (up to 32µm s-1 ) without the addition of any chemical fuels is developed. A light-triggered self-built electric field parallel to the light illumination exists due to asymmetrical surface chemical reactions induced by the limited penetration depth of light along the illumination. The phototactic motion of the motor is achieved through electrophoretic rotation induced by the asymmetrical distribution of zeta potential on the two hemispheres of the Janus micromotor, into alignment with the electric field. Notably, similar phototactic propulsion is also achieved on TiO2 /Pt and CdS/Pt micromotors, which presents explicit proof of extending the mechanism of dipole-moment induced phototactic propulsion in other light-driven Janus micromotors. Finally, active transportation of yeast cells are achieved by the motor, proving its capability in performing complex tasks.

Collective pattern formations of animals in active matter physics.

Active matter refers to systems composed of elements that are self-propelled by the dissipation of energy, in which dynamical patterns emerge, as is the case of flocks of birds and schools of fish. Some researchers in active matter physics seek to identify unified descriptions of such collective motions through interdisciplinary approaches by biologists and physicists. Through such collaborations, experimental studies pertaining to active matter physics have been developing recently, which allow us to verify the proposed mathematical models. Here, we review collective pattern formations and behaviors of animals from the perspective of active matter physics.

Fluctuations in Bacterial Suspensions Driven by Chemotaxis

Stochastic fluctuations in living systems create a spectacular variety of unique states far from equilibrium, which however remains largely unexplored regarding its underlying physics, especially when considering their instinctive responses to environmental stimuli. Here, by utilizing a molecular-dynamics model of bacterial chemotaxis, we present an investigation of tracer statistics in suspensions of chemotactic bacteria. Unlike Brownian motion in conventional media, the tracer particle performs a short-time ballistic but long-time Fickian diffusion with non-Gaussian dynamics. A phenomenological extension of Langevin equation accounts for the observed anomalous behaviors. Moreover, a violation of the Stokes-Einstein relation is identified regarding the size-dependence of particle diffusivity in bacterial suspensions. Our findings uncover the physical nature of stimulus-driven fluctuation statistics in bacterial fluids, and suggest a theoretical framework to deepen the understanding of the nonequilibrium statistical physics of active matter under external stimuli.

Compaction Dynamics during Progenitor Cell Self-Assembly Reveal Granular Mechanics

Summary We study the self-assembly dynamics of human progenitor cells in agarose microwells that are used for production of chondrogenic organoids. Using image analysis on time-lapse microscopy, we estimate the aggregate area in function of time for a large number of aggregates. In control conditions, the aggregate radius follows an exponential relaxation that is consistent with the dewetting dynamics of a liquid film. Upon introducing Y-27632 Rho kinase inhibitor, the compatibility with the liquid model is lost, and slowed-down relaxation dynamics are observed. We demonstrate that these aggregates behave as granular piles undergoing compaction, with density relaxation that follows a stretched exponential. Using simulations with an individual cell-based model, we construct a phase diagram of cell aggregates that suggests that the aggregate in presence of Rho kinase inhibitor approaches glass transition.

Dry Aligning Dilute Active Matter

Active matter physics is about systems in which energy is dissipated at some local level to produce work. This is a generic situation, particularly in the living world but not only. What is at stake is the understanding of the fascinating, sometimes counterintuitive, emerging phenomena observed, from collective motion in animal groups to in vitro dynamical self-organization of motor proteins and biofilaments. Dry aligning dilute active matter (DADAM) is a corner of the multidimensional, fast-growing domain of active matter that has both historical and theoretical importance for the entire field. This restrictive setting only involves self-propulsion/activity, alignment, and noise, yet unexpected collective properties can emerge from it. This review provides a personal but synthetic and coherent overview of DADAM, focusing on the collective-level phenomenology of simple active particle models representing basic classes of systems and on the solutions of the continuous hydrodynamic theories that can be derived from them. The obvious fact that orientational order is advected by the aligning active particles at play is shown to be at the root of the most striking properties of DADAM systems: ( a) direct transitions to orientational order are not observed; ( b) instead generic phase separation occurs with a coexistence phase involving inhomogeneous nonlinear structures; ( c) orientational order, which can be long range even in two dimensions, is accompanied by long-range correlations and anomalous fluctuations; ( d) defects are not point-like, topologically bound objects.

Pattern Formations in Active Matter Physics

Pattern Formations in Active Matter Physics

Unravelling the role of phoretic and hydrodynamic interactions in active colloidal suspensions.

Active fluids comprise a variety of systems composed of elements immersed in a fluid environment which can convert some form of energy into directed motion; as such they are intrinsically out-of-equilibrium in the absence of any external force. A fundamental problem in the physics of active matter concerns the understanding of how the characteristics of autonomous propulsion and agent-agent interactions determine the collective dynamics of the system. We study numerically the suspensions of self-propelled diffusiophoretic colloids, in (quasi)-2d configurations, accounting for both dynamically resolved solute-mediated phoretic interactions and solvent-mediated hydrodynamic interactions. Our results show that the system displays different scenarios at changing the colloid-solute affinity and it develops a cluster phase in the chemoattractive case. We study the statistics of cluster sizes and cluster morphologies for different magnitudes of colloidal activity. Finally, we provide evidences that hydrodynamics plays a relevant role in the aggregation kinetics and cluster morphology, significantly hindering cluster growth.

Self-Propulsion Strategies for Artificial Cell-Like Compartments.

Reconstitution of life-like properties in artificial cells is a current research frontier in synthetic biology. Mimicking metabolism, growth, and sensing are active areas of investigation; however, achieving motility and directional taxis are also challenging in the context of artificial cells. To tackle this problem, recent progress has been made that leverages the tools of active matter physics in synthetic biology. This review surveys the most significant achievements in designing motile cell-like compartments. In this context, strategies for self-propulsion are summarized, including, compartmentalization of catalytically active particles, phoretic propulsion of vesicles and emulsion droplet motion driven by Marangoni flows. This work showcases how the realization of motile protocells may impact biomedical engineering while also aiming at answering fundamental questions in locomotion of prebiotic cells.

Dynamical networks of worms

New experiments on swarms of Caenorhabditis elegans reveal that the worm can form a dynamical network that can be understood using active matter physics, and controlled using genetic manipulation.

C. elegans collectively forms dynamical networks

Understanding physical rules underlying collective motions requires perturbation of controllable parameters in self-propelled particles. However, controlling parameters in animals is generally not easy, which makes collective behaviours of animals elusive. Here, we report an experimental system in which a conventional model animal, Caenorhabditis elegans, collectively forms dynamical networks of bundle-shaped aggregates. We investigate the dependence of our experimental system on various extrinsic parameters (material of substrate, ambient humidity and density of worms). Taking advantage of well-established C. elegans genetics, we also control intrinsic parameters (genetically determined motility) by mutations and by forced neural activation via optogenetics. Furthermore, we develop a minimal agent-based model that reproduces the dynamical network formation and its dependence on the parameters, suggesting that the key factors are alignment of worms after collision and smooth turning. Our findings imply that the concepts of active matter physics may help us to understand biological functions of animal groups.

Directed Flow of Micromotors through Alignment Interactions with Micropatterned Ratchets.

To achieve control over naturally diffusive, out-of-equilibrium systems composed of self-propelled particles, such as cells or self-phoretic colloids, is a long-standing challenge in active matter physics. The inherently random motion of these active particles can be rectified in the presence of local and periodic asymmetric cues given that a nontrivial interaction exists between the self-propelled particle and the cues. Here, we exploit the phoretic and hydrodynamic interactions of synthetic micromotors with local topographical features to break the time-reversal symmetry of particle trajectories and to direct a macroscopic flow of micromotors. We show that the orientational alignment induced on the micromotors by the topographical features, together with their geometrical asymmetry, is crucial in generating directional particle flow. We also show that our system can be used to concentrate micromotors in confined spaces and identify the interactions leading to this effect. Finally, we develop a minimal model, which identifies the key parameters of the system responsible for the observed rectification. Overall, our system allows for robust control over both temporal and spatial distribution of synthetic micromotors.

Biophysics of Collective Phototaxis of Euglena gracilis

High-density suspensions of actively swimming cells in fluids often self-organize into complex dynamic patterns due to the interplay between microscopic force generation and macroscopic hydrodynamics. Though various biophysical models have been developed to describe the dynamics of these systems, experimental verification has been difficult to obtain. This is due to the complex interaction rules which govern the swimmer behavior, and the lack of tools for delivering controlled perturbations to a defined subset of cells inside such a suspension. Here, we consider concentrated suspensions of the unicellular, photoresponsive algae, Euglena gracilis. We propose an integrated experimental and theoretical platform for predicting the collective behavior of Euglena under light stimulation. By varying the spatiotemporal light patterns, we are able to finely adjust cell densities and achieve arbitrary non-homogeneous distributions, including compression into high-density aggregates of varying geometries. Our models were able to account for the light-induced aggregation that result from a complex interplay between negative phototaxis, hydrodynamic interactions, and shading effects between the cells. This work will deepen our general understanding of how relatively simple mechanical feedback interactions can generate multi-cell behaviors in microswimmer suspensions, and how to bridge such understanding over different length and time scales. Furthermore, it may also aid the engineering of microfluidic devices and advance concepts in active matter physics.

The statistical physics of active matter: From self-catalytic colloids to living cells

These lecture notes are designed to provide a brief introduction into the phenomenology of active matter and to present some of the analytical tools used to rationalize the emergent behavior of active systems. Such systems are made of interacting agents able to extract energy stored in the environment to produce sustained directed motion. The local conversion of energy into mechanical work drives the system far from equilibrium, yielding new dynamics and phases. The emerging phenomena can be classified depending on the symmetry of the active particles and on the type of microscopic interactions. We focus here on steric and aligning interactions, as well as interactions driven by shape changes. The models that we present are all inspired by experimental realizations of either synthetic, biomimetic or living systems. Based on minimal ingredients, they are meant to bring a simple and synthetic understanding of the complex phenomenology of active matter.

An introduction to the statistical physics of active matter: motility-induced phase separation and the “generic instability” of active gels

In this work we review some statistical physics techniques to coarse grain active matter systems, writing down a set of continuum fields which track the evolution of macroscopic fields such as density, momentum, etc. While the method can be applied in general, we will focus here on two simple and by now well-studied, active matter examples. First, we will consider motility-induced phase separation, the phenomenon by which a concentrated suspension of self-propelled particles spontaneously separates into a dense and a dilute phase. Second, we will review the so-called “generic instability” of active gels, which refers to the nonequilibrium phase transition between a quiescent and a spontaneously flowing phase in a concentrated suspension of rodlike active particles. For both these cases, we also outline recent developments in the literature.

An improved Cellular Automata model to simulate the behavior of high density crowd and validation by experimental data

In this article we present an improved version of the Cellular Automata floor field model making use of a sub-mesh system to increase the maximum density allowed during simulation and reproduce phenomena observed in dense crowds. In order to calibrate the model’s parameters and to validate it we used data obtained from an empirical observation of bidirectional pedestrian flow. A good agreement was found between numerical simulation and experimental data and, in particular, the double outflow peak observed during the formation of deadlocks could be reproduced in numerical simulations, thus allowing the analysis of deadlock formation and dissolution. Finally, we used the developed high density model to compute the flow-ratio dependent fundamental diagram of bidirectional flow, demonstrating the instability of balanced flow and predicting the bidirectional flow behavior at very high densities. The model we presented here can be used to prevent dense crowd accidents in the future and to investigate the dynamics of the accidents which already occurred in the past. Additionally, fields such as granular and active matter physics may benefit from the developed framework to study different collective phenomena.

Fast Magnetic Micropropellers with Random Shapes.

Studying propulsion mechanisms in low Reynolds number fluid has implications for many fields, ranging from the biology of motile microorganisms and the physics of active matter to micromixing in catalysis and micro- and nanorobotics. The propulsion of magnetic micropropellers can be characterized by a dimensionless speed, which solely depends on the propeller geometry for a given axis of rotation. However, this dependence has so far been only investigated for helical propeller shapes, which were assumed to be optimal. In order to explore a larger variety of shapes, we experimentally studied the propulsion properties of randomly shaped magnetic micropropellers. Surprisingly, we found that their dimensionless speeds are high on average, comparable to previously reported nanofabricated helical micropropellers. The highest dimensionless speed we observed is higher than that of any previously reported propeller moving in a low Reynolds number fluid, proving that physical random shape generation can be a viable optimization strategy.

An introduction to the physics of active matter

In these notes we provide an introductory description of the physics of active matter, focusing on theoretical aspects, and on some methods which are often used in the field. We discuss a selection of active systems, where activity comes from different microscopic sources (mainly self-replication, self-propulsion, non-thermal forces), and in all cases we focus on their statistical physics and emergent collective behaviour, which is often linked to underlying nonequilibrium phase transitions. We hope to convey the idea that this field is a fascinating growing area of research at the interphase between statistical, soft matter and biological physics, and that active matter systems can possess, in general, a much richer physics than their passive counterparts.