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Various types of structures self-organised by animals exist in nature, such as bird flocks and insect swarms, which stem from the local communications of vast numbers of limited individuals. Through the designing of algorithms and wireless communication, robotic systems can emulate some complex swarm structures in nature. However, creating a swarming robotic system at the microscale that embodies functional collective behaviours remains a challenge. Herein, we report a strategy to reconfigure paramagnetic nanoparticles into ribbon-like swarms using oscillating magnetic fields, and the mechanisms are analysed. By tuning the input fields, the microswarm can perform a reversible elongation with an extremely high aspect ratio, as well as splitting and merging. Moreover, we investigate the behaviours of the microswarm when it encounters solid boundaries, and demonstrate that under navigation, the colloidal microswarm passes through confined channel networks towards multiple targets with high access rates and high swarming pattern stability. Manipulation of paramagnetic microparticles can be exploited for drug delivery. Here the authors manipulate a swarm of such particles and control its shape with a magnetic field so that it can elongate reversibly, split into smaller swarms and thus be guided through a maze with multiple parallel channels.

From political dissenters to impurities in crystals, intuition tells us that pockets of disruption discourage cooperation and promote disordered behaviour in groups of people or particles. A unifying property of active matter is that the energy consumption of these systems keeps them far from equilibrium - for birds and bacteria alike, equilibrium means death. Using statistical-physics techniques, and equations that are typically used to model swarming behaviour in 2D living systems, the authors measured long-range polar order, which describes the tendency for swarmers to align with other agents in terms of the average velocity of the swarm (Fig. 1).

The comprehension of how local interactions arise in global collective behavior is of utmost importance in both biological and physical research. Traditional agent-based models often rely on static rules that fail to capture the dynamic strategies of the biological world. Reinforcement learning (RL) has been proposed as a solution, but most previous methods adopt handcrafted reward functions that implicitly or explicitly encourage the emergence of swarming behaviors. In this study, we propose a minimal predator–prey coevolution framework based on mixed cooperative–competitive multiagent RL, and adopt a reward function that is solely based on the fundamental survival pressure, that is, prey receive a reward of −1 if caught by predators while predators receive a reward of +1. Surprisingly, our analysis of this approach reveals an unexpectedly rich diversity of emergent behaviors for both prey and predators, including flocking and swirling behaviors for prey, as well as dispersion tactics, confusion, and marginal predation phenomena for predators. Overall, our study provides novel insights into the collective behavior of organisms and highlights the potential applications in swarm robotics.

Effective management of insect disease vectors requires a detailed understanding of their ecology and behavior. In Anopheles gambiae sensu lato (s.l.) (Diptera: Culicidae) mating occurs during swarming, but knowledge of their mating behavior under natural conditions is limited. Mosquitoes mate in flight over specific landmarks, known as swarm markers, at particular locations. Swarms consist of males; the females usually approach the swarm and depart following copulation. The number of mating pairs per swarm is closely associated with swarm size. The shape and height of swarm markers vary and may depend on the environmental conditions at the swarm's location. Male–male interactions in mosquito swarms with similar levels of attractive flight activity can offer a mating advantage to some individuals. Flight tone is used by mosquitoes to recognize the other sex and choose a desirable mate. Clarifying these and other aspects of mosquito reproductive behavior can facilitate the development of population control measures that target swarming sites. This review describes what is currently known about swarming behavior in Anopheles gambiae s.l., including swarm characteristics; mating within and outside of swarms, insemination in females, and factors affecting and stimulating swarming.

The development of artificial small-scale robotic swarms with nature-mimicking collective behaviors represents the frontier of research in robotics. While microrobot swarming under magnetic manipulation has been extensively explored, light-induced self-organization of micro- and nanorobots is still challenging. This study demonstrates the interaction-controlled, reconfigurable, reversible, and active self-assembly of TiO 2 /α-Fe 2 O 3 microrobots, consisting of peanut-shaped α-Fe 2 O 3 (hematite) microparticles synthesized by a hydrothermal method and covered with a thin layer of TiO 2 by atomic layer deposition (ALD). Due to their photocatalytic and ferromagnetic properties, microrobots autonomously move in water under light irradiation, while a magnetic field precisely controls their direction. In the presence of H 2 O 2 fuel, concentration gradients around the illuminated microrobots result in mutual attraction by phoretic interactions, inducing their spontaneous organization into self-propelled clusters. In the dark, clusters reversibly reconfigure into microchains where microrobots are aligned due to magnetic dipole-dipole interactions. Microrobots’ active motion and photocatalytic properties were investigated for water remediation from pesticides, obtaining the rapid degradation of the extensively used, persistent, and hazardous herbicide 2,4-Dichlorophenoxyacetic acid (2,4D). This study potentially impacts the realization of future intelligent adaptive metamachines and the application of light-powered self-propelled micro- and nanomotors toward the degradation of persistent organic pollutants (POPs) or micro- and nanoplastics. Microrobot collectives promise new functions beyond individuals’ capability. Here, nature-inspired reconfigurable self-assembly of microrobots was created, driven by their photocatalytic and magnetic properties, showing potential application in water purification.

In nature, swarming behavior has evolved repeatedly among motile organisms because it confers a variety of beneficial emergent properties. These include improved information gathering, protection from predators, and resource utilization. Some organisms, e.g., locusts, switch between solitary and swarm behavior in response to external stimuli. Aspects of swarming behavior have been demonstrated for motile supramolecular systems composed of biomolecular motors and cytoskeletal filaments, where cross-linkers induce large scale organization. The capabilities of such supramolecular systems may be further extended if the swarming behavior can be programmed and controlled. Here, we demonstrate that the swarming of DNA-functionalized microtubules (MTs) propelled by surface-adhered kinesin motors can be programmed and reversibly regulated by DNA signals. Emergent swarm behavior, such as translational and circular motion, can be selected by tuning the MT stiffness. Photoresponsive DNA containing azobenzene groups enables switching between solitary and swarm behavior in response to stimulation with visible or ultraviolet light. Self-propelled molecular entities enable studying swarm behavior on a macroscopic scale but programmability of interactions has yet not been achieved. Here the authors show reversible regulation of DNA-functionalized microtubules by DNA signals and switching between solitary and swarm behaviour by employing photoresponsive DNA strands.

The biological carbon pump drives a flux of particulate organic carbon (POC) through the ocean and affects atmospheric levels of carbon dioxide. Short term, episodic flux events are hard to capture with current observational techniques and may thus be underrepresented in POC flux estimates. We model the potential hidden flux of POC originating from Antarctic krill, whose swarming behaviour could result in a major conduit of carbon to depth through their rapid exploitation of phytoplankton blooms and bulk egestion of rapidly sinking faecal pellets (FPs). Our model results suggest a seasonal krill FP export flux of 0.039 GT C across the Southern Ocean marginal ice zone, corresponding to 17–61% (mean 35%) of current satellite-derived export estimates for this zone. The magnitude of our conservatively estimated flux highlights the important role of large, swarming macrozooplankton in POC export and, the need to incorporate such processes more mechanistically to improve model projections. Particulate organic carbon (POC) fluxes in the oceans, particularly the Southern Ocean, remain poorly constrained. Here the authors modelled the potential underestimated flux of POC originating from Antarctic krill and discovered a seasonal krill faecal pellet export flux of 0.039 GT C yr-1 across the marginal ice zone (MIZ) of the Southern Ocean.

Swarmalators are entities with the simultaneous presence of swarming and synchronization that reveal emergent collective behavior due to the fascinating bidirectional interplay between phase and spatial dynamics. Although different coupling topologies have already been considered, here we introduce time-varying competitive phase interaction among swarmalators where the underlying connectivity for attractive and repulsive coupling varies depending on the vision (sensing) radius. Apart from investigating some fundamental properties like conservation of center of position and collision avoidance, we also scrutinize the cases of extreme limits of vision radius. The concurrence of attractive–repulsive competitive phase coupling allows the exploration of diverse asymptotic states, like static π , and mixed phase wave states, and we explore the feasible routes of those states through a detailed numerical analysis. In sole presence of attractive local coupling, we reveal the occurrence of static cluster synchronization where the number of clusters depends crucially on the initial distribution of positions and phases of each swarmalator. In addition, we analytically calculate the sufficient condition for the emergence of the static synchronization state. We further report the appearance of the static ring phase wave state and evaluate its radius theoretically. Finally, we validate our findings using Stuart–Landau oscillators to describe the phase dynamics of swarmalators subject to attractive local coupling.

Living systems at all scales aggregate in large numbers for a variety of functions including mating, predation, and survival. The majority of such systems consist of unconnected individuals that collectively flock, school, or swarm. However, some aggregations involve physically entangled individuals, which can confer emergent mechanofunctional material properties to the collective. Here, we study in laboratory experiments and rationalize in theoretical and robophysical models the dynamics of physically entangled and motile self-assemblies of 1-cm-long California blackworms (Lumbriculus variegatus, Annelida: Clitellata: Lumbriculidae). Thousands of individual worms form braids with their long, slender, and flexible bodies to make a three-dimensional, soft, and shape-shifting “blob.” The blob behaves as a living material capable of mitigating damage and assault from environmental stresses through dynamic shape transformations, including minimizing surface area for survival against desiccation and enabling transport (negative thermotaxis) from hazardous environments (like heat). We specifically focus on the locomotion of the blob to understand how an amorphous entangled ball of worms can break symmetry to move across a substrate. We hypothesize that the collective blob displays rudimentary differentiation of function across itself, which when combined with entanglement dynamics facilitates directed persistent blob locomotion. To test this, we develop a robophysical model of the worm blobs, which displays emergent locomotion in the collective without sophisticated control or programming of any individual robot. The emergent dynamics of the living functional blob and robophysical model can inform the design of additional classes of adaptive mechanofunctional living materials and emergent robotics.

Countless times each day, the acute inflammatory response protects us from invading microbes, injuries, and insults from within, as in surgery-induced tissue injury. These challenges go unnoticed because they are self-limited and naturally resolve without progressing to chronic inflammation. Peripheral blood markers of inflammation are present in many common diseases, including inflammatory bowel disease, cardiovascular disease, neurodegenerative disease, and cancer. While acute inflammation is protective, excessive swarming of neutrophils amplifies collateral tissue damage and inflammation. Hence, understanding the mechanisms that control the resolution of acute inflammation provides insight into preventing and treating inflammatory diseases in multiple organs. This Review focuses on the resolution phase of inflammation with identification of specialized pro-resolving mediators (SPMs) that involve three separate biosynthetic and potent mediator families, which are defined using the first quantitative resolution indices to score this vital process. These are the resolvins, protectins, and maresins: bioactive metabolomes that each stimulate self-limited innate responses, enhance innate microbial killing and clearance, and are organ-protective. We briefly address biosynthesis of SPMs and their activation of endogenous resolution programs as terrain for new therapeutic approaches that are not, by definition, immunosuppressive, but rather new immunoresolvent therapies.