Multi-scale organization in communicating active matter

Interplay of chemotactic force, Péclet number, and dimensionality dictates the dynamics of auto-chemotactic chiral active droplets

In living and synthetic active matter systems, the constituents can self-propel and interact with each other and with the environment through various physicochemical mechanisms. Among these mechanisms, chemotactic and auto-chemotactic effects are widely observed. The impact of (auto-)chemotactic effects on achiral active matter has been a recent research focus. However, the influence of these effects on chiral active matter remains elusive. Here, we develop a Brownian dynamics model coupled with a diffusion equation to examine the dynamics of auto-chemotactic chiral active droplets in both quasi-two-dimensional (2D) and three-dimensional (3D) systems. By quantifying the droplet trajectory as a function of the dimensionless Péclet number and chemotactic strength, our simulations well reproduce the curling and helical trajectories of nematic droplets in a surfactant-rich solution reported by Krüger et al. [Phys. Rev. Lett. 117, 048003 (2016)]. The modeled curling trajectory in 2D exhibits an emergent chirality, also consistent with the experiment. We further show that the geometry of the chiral droplet trajectories, characterized by the pitch and diameter, can be used to infer the velocities of the droplet. Interestingly, we find that, unlike the achiral case, the velocities of chiral active droplets show dimensionality dependence: its mean instantaneous velocity is higher in 3D than in 2D, whereas its mean migration velocity is lower in 3D than in 2D. Taken together, our particle-based simulations provide new insights into the dynamics of auto-chemotactic chiral active droplets, reveal the effects of dimensionality, and pave the way toward their applications, such as drug delivery, sensors, and micro-reactors.

Chemical Logic Gates on Active Colloids

Recent studies have shown that active colloidal motors using enzymatic reactions for propulsion hold special promise for applications in fields ranging from biology to material science. It will be desirable to have active colloids with capability of computation so that they can act autonomously to sense their surroundings and alter their own dynamics. It is shown how small chemical networks that make use of enzymatic chemical reactions on the colloid surface can be used to construct motor-based chemical logic gates. The basic features of coupled enzymatic reactions that are responsible for propulsion and underlie the construction and function of chemical gates are described using continuum theory and molecular simulation. Examples are given that show how colloids with specific chemical logic gates, can perform simple sensing tasks. Due to the diverse functions of different enzyme gates, operating alone or in circuits, the work presented here supports the suggestion that synthetic motors using such gates could be designed to operate in an autonomous way in order to complete complicated tasks.

Swarm Autonomy: From Agent Functionalization to Machine Intelligence

Swarm behaviors are common in nature, where individual organisms collaborate via perception, communication, and adaptation. Emulating these dynamics, large groups of active agents can self-organize through localized interactions, giving rise to complex swarm behaviors, which exhibit potential for applications across various domains. This review presents a comprehensive summary and perspective of synthetic swarms, to bridge the gap between the microscale individual agents and potential applications of synthetic swarms. It is begun by examining active agents, the fundamental units of synthetic swarms, to understand the origins of their motility and functionality in the presence of external stimuli. Then inter-agent communications and agent-environment communications that contribute to the swarm generation are summarized. Furthermore, the swarm behaviors reported to date and the emergence of machine intelligence within these behaviors are reviewed. Eventually, the applications enabled by distinct synthetic swarms are summarized. By discussing the emergent machine intelligence in swarm behaviors, insights are offered into the design and deployment of autonomous synthetic swarms for real-world applications.

Collective self-optimization of binary mixed heterogeneous populations

To maximize the survival chances of society members, collective self-organization must balance individual interests with promoting the collective welfare. Although situations where group members have equal optimal values are clear, how varying optimal values impacts group dynamics remains unclear. To address this gap, we conducted a self-optimization study of a binary system incorporating communication-enabled active particles with distinct optimal values. We demonstrate that similar particles will spontaneously aggregate and separate from each other to maximize their individual benefits during the process of self-optimization. Our research shows that both types of particles can produce the optimal field values at low density. However, only one type of particle can achieve the optimal field values at medium density. At high densities, neither type of particle is effective in reaching the optimal field values. Interestingly, we observed that during the self-optimization process, the mixture demixed spontaneously under certain circumstances of mixed particles. Particles with higher optimal values developed into larger clusters, while particles with lower optimal values migrated outside of these clusters, resulting in the separation of the mixture. To achieve this separation, suitable noise intensity, particle density, and the significant difference in optimal values were necessary. Our results provide a more profound comprehension of the self-optimization of synthetic or biological agents' communication and provide valuable insight into separating binary species and mixtures.

Local control for the collective dynamics of self-propelled particles

Utilizing a paradigmatic model for the motion of interacting self-propelled particles, we demonstrate that local accelerations at the level of individual particles can drive transitions between different collective dynamics, leading to a control process. We find that the ability to trigger such transitions is hierarchically distributed among the particles and can form distinctive spatial patterns within the collective. Chaotic dynamics occur during the transitions, which can be attributed to fractal basin boundaries mediating the control process. The particle hierarchies described in this paper offer decentralized capabilities for controlling artificial swarms.

Complex motion of steerable vesicular robots filled with active colloidal rods

While the collective motion of active particles has been studied extensively, effective strategies to navigate particle swarms without external guidance remain elusive. We introduce a method to control the trajectories of two-dimensional swarms of active rod-like particles by confining the particles to rigid bounding membranes (vesicles) with non-uniform curvature. We show that the propelling agents spontaneously form clusters at the membrane wall and collectively propel the vesicle, turning it into an active superstructure. To further guide the motion of the superstructure, we add discontinuous features to the rigid membrane boundary in the form of a kinked tip, which acts as a steering component to direct the motion of the vesicle. We report that the system's geometrical and material properties, such as the aspect ratio and Péclet number of the active rods as well as the kink angle and flexibility of the membrane, determine the stacking of active particles close to the kinked confinement and induce a diverse set of dynamical behaviors of the superstructure, including linear and circular motion both in the direction of, and opposite to, the kink. From a systematic study of these various behaviors, we design vesicles with switchable and reversible locomotions by tuning the confinement parameters. The observed phenomena suggest a promising mechanism for particle transportation and could be used as a basic element to navigate active matter through complex and tortuous environments.

Motility-Induced Phase Separation Mediated by Bacterial Quorum Sensing

We study motility-induced phase separation (MIPS) in living active matter, in which cells interact through chemical signaling, or quorum sensing. In contrast to previous theories of MIPS, our multiscale continuum model accounts explicitly for genetic regulation of signal production and motility. Through analysis and simulations, we derive a new criterion for the onset of MIPS that depends on features of the genetic network. Furthermore, we identify and characterize a new type of oscillatory instability that occurs when gene regulation inside cells promotes motility in higher signal concentrations.

Hierarchical defect-induced condensation in active nematics

Topological defects play a central role in the formation and organization of various biological systems. Historically, such nonequilibrium defects have been mainly studied in the context of homogeneous active nematics. Phase-separated systems, in turn, are known to form dense and dynamic nematic bands, but typically lack topological defects. In this paper, we use agent-based simulations of weakly aligning, self-propelled polymers and demonstrate that contrary to the existing paradigm phase-separated active nematics form -1/2 defects. Moreover, these defects, emerging due to interactions among dense nematic bands, constitute a novel second-order collective state. We investigate the morphology of defects in detail and find that their cores correspond to a strong increase in density, associated with a condensation of nematic fluxes. Unlike their analogs in homogeneous systems, such condensed defects form and decay in a different way and do not involve positively charged partners. We additionally observe and characterize lateral arc-like structures that separate from a band's bulk and move in transverse direction. We show that the key control parameters defining the route from stable bands to the coexistence of dynamic lanes and defects are the total density of particles and their path persistence length. We introduce a hydrodynamic theory that qualitatively recapitulates all the main features of the agent-based model, and use it to show that the emergence of both defects and arcs can be attributed to the same anisotropic active fluxes. Finally, we present a way to artificially engineer and position defects, and speculate about experimental verification of the provided model.

pH-Responsive swimming behavior of light-powered rod-shaped micromotors

Micromotors have emerged as promising devices for a wide range of applications e.g., microfluidics, lab-on-a-chip devices, active matter, environmental monitoring, etc. The control over the activity of micromotors with the ability to exhibit multimode swimming is one of the most desirable features for many of the applications. Here, we demonstrate a rod-shaped light-driven micromotor whose activity and swimming behavior can easily be controlled. The rod-shaped micromotors are fabricated through the dynamic shadowing growth (DSG) technique, where a 2 μm long arm of titanium dioxide (TiO2) is grown over spherical silica (SiO2) particles (1 μm diameter). Under low-intensity UV light exposure, the micromotors exhibit self-propulsion in an aqueous peroxide medium. When activated, the swimming behavior of micromotors greatly depends on the pH of the medium. The swimming direction, i.e., forward or backward movement, as well as swimming modes like translational or rotational motion, can be controlled by changing the pH values. The observed dynamics has been rationalized using a theoretical model incorporating chemical activity, hydrodynamic flow, and the effect of gravity for a rod-shaped active particle near a planar wall. The pH-dependent translational and rotational dynamics of micromotors provide a versatile platform for achieving controlled and responsive behaviors. Continued research and development in this area hold great promise for advancing micromotors and enabling novel applications in microfluidics, micromachining, environmental sciences, and biomedicine.

Spontaneous shock waves in pulse-stimulated flocks of Quincke rollers

Active matter demonstrates complex spatiotemporal self-organization not accessible at equilibrium and the emergence of collective behavior. Fluids comprised of microscopic Quincke rollers represent a popular realization of synthetic active matter. Temporal activity modulations, realized by modulated external electric fields, represent an effective tool to expand the variety of accessible dynamic states in active ensembles. Here, we report on the emergence of shockwave patterns composed of coherently moving particles energized by a pulsed electric field. The shockwaves emerge spontaneously and move faster than the average particle speed. Combining experiments, theory, and simulations, we demonstrate that the shockwaves originate from intermittent spontaneous vortex cores due to a vortex meandering instability. They occur when the rollers' translational and rotational decoherence times, regulated by the electric pulse durations, become comparable. The phenomenon does not rely on the presence of confinement, and multiple shock waves continuously arise and vanish in the system.

Cell behaviors underlying Myxococcus xanthus aggregate dispersal

IMPORTANCE

Understanding the processes behind bacterial biofilm formation, maintenance, and dispersal is essential for addressing their effects on health and ecology. Within these multicellular communities, various cues can trigger differentiation into distinct cell types, allowing cells to adapt to their specific local environment. The soil bacterium Myxococcus xanthus forms biofilms in response to starvation, marked by cells aggregating into mounds. Some aggregates persist as spore-filled fruiting bodies, while others disperse after initial formation for unknown reasons. Here, we use a combination of cell tracking analysis and computational simulations to identify behaviors at the cellular level that contribute to aggregate dispersal. Our results suggest that cells in aggregates actively determine whether to disperse or persist and undergo a transition to sporulation based on a self-produced cue related to the aggregate size. Identifying these cues is an important step in understanding and potentially manipulating bacterial cell-fate decisions.

Chemotactic Motility-Induced Phase Separation

Collectives of actively moving particles can spontaneously separate into dilute and dense phases-a fascinating phenomenon known as motility-induced phase separation (MIPS). MIPS is well-studied for randomly moving particles with no directional bias. However, many forms of active matter exhibit collective chemotaxis, directed motion along a chemical gradient that the constituent particles can generate themselves. Here, using theory and simulations, we demonstrate that collective chemotaxis strongly competes with MIPS-in some cases, arresting or completely suppressing phase separation, or in other cases, generating fundamentally new dynamic instabilities. We establish principles describing this competition, thereby helping to reveal and clarify the rich physics underlying active matter systems that perform chemotaxis, ranging from cells to robots.

Anomalous Collective Dynamics of Autochemotactic Populations

While the role of local interactions in nonequilibrium phase transitions is well studied, a fundamental understanding of the effects of long-range interactions is lacking. We study the critical dynamics of reproducing agents subject to autochemotactic interactions and limited resources. A renormalization group analysis reveals distinct scaling regimes for fast (attractive or repulsive) interactions; for slow signal transduction, the dynamics is dominated by a diffusive fixed point. Furthermore, we present a correction to the Keller-Segel nonlinearity emerging close to the extinction threshold and a novel nonlinear mechanism that stabilizes the continuous transition against the emergence of a characteristic length scale due to a chemotactic collapse.

Active control of equilibrium, near-equilibrium, and far-from-equilibrium colloidal systems

The development of top-down active control over bottom-up colloidal assembly processes has the potential to produce materials, surfaces, and objects with applications in a wide range of fields spanning from computing to materials science to biomedical engineering. In this review, we summarize recent progress in the field using a taxonomy based on how active control is used to guide assembly. We find there are three distinct scenarios: (1) navigating kinetic pathways to reach a desirable equilibrium state, (2) the creation of a desirable metastable, kinetically trapped, or kinetically arrested state, and (3) the creation of a desirable far-from-equilibrium state through continuous energy input. We review seminal works within this framework, provide a summary of important application areas, and present a brief introduction to the fundamental concepts of control theory that are necessary for the soft materials community to understand this literature. In addition, we outline current and potential future applications of actively-controlled colloidal systems, and we highlight important open questions and future directions.

Mechanochemical feedback loops in contact-dependent fate patterning

To reliably form and maintain structures with specific functions, many multicellular systems evolved to leverage the interplay between biochemical signaling, mechanics, and morphology. We review mechanochemical feedback loops in cases where cell-cell contact-based Notch signaling drives fate decisions, and the corresponding differentiation process leads to contact remodeling. We compare different mechanisms for initial symmetry breaking and subsequent pattern refinement, as well as discuss how patterning outcomes depend on the relationship between biochemical and mechanical timescales. We conclude with an overview of new approaches, including the study of synthetic circuits, and give an outlook on future experimental and theoretical developments toward dissecting and harnessing mechanochemical feedback.