Many animal groups form structures such as flocks and swarms. However, how can the individual agents reconcile the simultaneous requirements of local collision avoidance, alignment, and group cohesion to achieve coherent collective motion? Here, we propose a minimal flocking model, where each agent is capable of vision-based steering interactions to achieve these (conflicting) goals. Numerical simulations in two dimensions show that local collision avoidance acts as a source for emergent noise and induces an order-disorder transition, triggered by the fast response of the flock to local directional changes. The emergence of large vortices at the critical point hints at a Berezinskii-Kosterlitz-Thouless-like transition. Deep in the ordered phase, the cohesion acts like a surface tension, favouring compact flock shapes. The competing interactions lead to pronounced shape and density fluctuations of the flock. These large fluctuations can be important for a fast response to external cues, which aids predator evasion and foraging. The collective dynamics of active swarms such as bird flocks and fish schools emerge from the complex, and often competing, interaction involving alignment, cohesion and collision avoidance. The authors propose a minimal flocking model with vison-based steering interactions, revealing a unique transition from order to disorder reminiscent of a Berezinskii-Kosterlitz-Thouless transition, which could enhance understanding of rapid flock responses in biological systems.

The wobbling motion of flagellated bacteria significantly influences their swimming behavior, yet its dynamics remains poorly understood, primarily due to the difficulty in tracking the 3D orientations of both the flagellar bundle and the cell body. Here, we use hydrodynamics simulations of a mechanical Escherichia coli model in polymer fluids with varying wobbling amplitudes and flagellar anchoring configurations to elucidate this motion. Through Euler angle analysis, we resolve the three components of wobbling: precession, nutation, and spin. Our findings challenge the common assumption that peritrichous bacteria undergo complete cycles of body spin. Notably, we uncover a small-amplitude nutation with a well-defined period on the order of a few milliseconds. We also identify two distinct precession modes. To interpret these findings, we develop a theoretical framework based on Lagrangian mechanics.

The mechanisms behind collision avoidance and its effects in pedestrian streams are not yet fully understood. In crossing multi-directional streams it can lead to self-organisation phenomena. A prominent example is lane formation in counterflow. Here we study a symmetric 3-way intersection using methods from active particle systems theory. A rich phase diagram with four different phases is found as function of the maneuverability and vision angle of the agents. The properties of the phases are rather different and should be distinguishable experimentally.

Motile microorganisms often navigate crowded and structurally complex environments, where surrounding obstacles can strongly influence locomotion. The bloodstream form of the flagellate parasite Trypanosoma brucei circulates in blood, a dense suspension of red blood cells (RBCs), yet the physical mechanisms governing its locomotion under such conditions remain poorly understood because direct experimental observations are challenging. Here, we combine numerical simulations with in vitro experiments to investigate trypanosome motility in concentrated RBC suspensions and in suspensions of spherical colloidal particles. Simulations reveal that the parasite swimming speed increases by up to 50% at RBC volume fractions comparable to those in blood. To identify the origin of this enhancement, we perform controlled studies in colloidal suspensions with particles of different sizes. We find that suspended particles substantially increase the anisotropy between the perpendicular and parallel friction coefficients acting on the beating flagellum, thereby enhancing propulsion. This effect is most pronounced when the suspended particles are comparable to or smaller than the characteristic wavelength of the flagellar beat. Experiments with microparticle suspensions confirm an increase in trypanosome propulsion with increasing particle concentration, in qualitative agreement with the simulations. Our results uncover a general physical mechanism by which concentrated particle suspensions can enhance flagellar-beat-driven locomotion and suggest that the densely crowded, particulate environment of blood may facilitate trypanosome propulsion. These findings provide new insight into trypanosome motility in the bloodstream and may apply broadly to other flagellated microswimmers in complex suspensions.

Primary hemostasis is initiated by platelet adhesion and aggregation at a site of vascular injury and is strongly regulated by local hydrodynamic conditions. At elevated shear rates, platelet capture is mediated by von Willebrand factor (vWF), a multimeric protein that undergoes shear-induced unfolding and becomes adhesive. We investigate early-stage clot formation under physiological high-shear-flow conditions by employing particle-based mesoscale hydrodynamics simulations with explicitly resolved red blood cells, platelets, and mechano-sensitive vWF in a microchannel geometry. The model incorporates vWF-mediated adhesion of platelets to a hemostatic surface, together with non-periodic inflow-outflow boundary conditions that allow continuous material supply and transport. We analyze the dynamics of platelet-vWF aggregation, clot growth dynamics, clot geometry and internal stresses, and thrombo-embolization across a range of elevated flow rates. Our results demonstrate that clot formation proceeds through the establishment of platelet-vWF aggregates at the hemostatic site, and that the clot reaches a finite size determined solely by hydrodynamic forces, without invoking biochemical stabilization mechanisms. Beyond a critical size, increased drag from fluid flow leads to recurrent embolization events that limit further growth. These findings highlight the central role of hydrodynamic stresses in regulating primary hemostasis and provide a mechanistic framework for understanding clot stability under physiological flow conditions.

Intelligent active particles are characterized by self-propulsion, directional sensing of their environment, information processing, decision making and goal-oriented self-steering. This implies, in particular, the prevalence of non-reciprocal interactions, and the importance of information propagation through agent groups. Examples include biological systems (cells, insects, birds, fish, pedestrians) as well as engineered systems (nano- and microbots). As many agents move in an aqueous medium, hydrodynamic interactions strongly affect the dynamics. The emergent dynamics includes the formation of swarms and flocks, predator-prey behavior, and the navigation in complex environments.

The pursuit‐evasion game is studied for two adversarial active agents, modeled as a deterministic self‐steering pursuer and a stochastic, cognitive evader. The pursuer chases the evader by reorienting its propulsion direction with limited maneuverability, while the evader escapes by executing sharp, unpredictable turns, whose timing and direction the pursuer cannot anticipate. To make the target responsive and agile when the threat level is high, the tumbling frequency is set to increase with decreasing distance from the pursuer; furthermore, the range of preferred tumbling directions is varied. Numerical simulations of such a pursuer–target pair in two spatial dimensions reveal two important scenarios. For dominant pursuers, the evader is compelled to adopt a high‐risk strategy that allows the pursuer to approach closely before the evader executes a potentially game‐changing backward maneuver to pull away from the pursuer. Otherwise, a strategy where the evader tumbles forward with continuous slight adjustments of the propulsion direction can significantly increase the capture time by preventing the pursuer from aligning with the target propulsion direction while maintaining the persistence of the target motion. Our results can guide the design of bioinspired robotic systems with efficient evasion capabilities.

The fast and efficient directed motion of particles through crowded environments is challenging problem. In this work, the surface-bound motion of an intruder in a crowd of identical active agents is studied by overdamped Langevin dynamics simulations. Both intruder and agents are modeled as intelligent active Brownian particles (iABPs) with visual perception and directional steering to avoid collisions - which implies non-reciprocal interactions between all particles. The reorientation of intruder and agents is limited by their maximal maneuverability, which controls the ability of an iABP to adjust its velocity direction. The simulation results show that the intruder’s attempt to increase directional speed by steering around agents fails; in fact, this even reduces the directional speed. In contrast, the intruder has to be perceived by the agents so that they can move out of the way in time. The intruder speed and transverse diffusivity are determined as functions of several key control parameters, like maneuverability, vision angle, and agent density. Here, an important parameter is the uniformity of the agent distribution. It is shown that the agent’s self-steering to avoid collision enhances hyperuniformity (class III), which facilitates an easier directional navigation of the intruder. Results are relevant, inter alia, for the motion of emergency personnel in semi-dense human crowds.

The collective properties of a binary mixture of A - and B -type self-steering particles endowed with visual perception are studied by computer simulations. Active Brownian particles (ABPs) are employed with an additional steering mechanism, which enables them to adjust their propulsion direction relative to the instantaneous positions of neighboring particles, depending on the species, either steering toward or away from them. Steering can be nonreciprocal, in particular between the A - and B -type particles. The underlying dynamical and structural properties of the system are governed by the strength and polarity of the maneuverabilities (i.e. maximum reorientation torques) associated with the vision-induced steering. The model predicts the emergence of a large variety of nonequilibrium behaviors, which we systematically characterize for all nine principal sign combinations of AA , BB , AB and BA maneuverabilites. In particular, we observe the formation of multimers, encapsulated aggregates, honeycomb lattices, and predator-prey pursuit. Notably, for a predator-prey system, the maneuverability and vision angle employed by a predator significantly impacts the spatial distribution of the surrounding prey particles. For systems with electric-charge-like interactions (i.e. like-particles repel, unlike attract) and nonstoichiometric composition (i.e. small number excess of one component), we obtain at intermediate activity levels an enhanced diffusion compared to non-steering ABPs.

Margination is a physical phenomenon that describes the migration of cells and particles toward vessel walls in blood flow, and thus, it serves as a necessary precondition for the adhesion of particles suspended in blood plasma to the endothelium. In the context of malaria, adhesion of infected red blood cells (iRBCs) to the endothelium is essential for the disease progression, as iRBCs have to evade the removal from the blood circulation in the spleen. Some malaria strains lead to the formation of rosettes, multicellular structures composed of one iRBC surrounded by several adhered healthy RBCs (hRBCs). We employ mesoscopic hydrodynamics simulations and microfluidic experiments to investigate the margination of rosettes in blood flow at various flow rates, volume fractions of hRBCs, and binding strengths between iRBCs and hRBCs. Surprisingly, rosette margination is significantly weaker than that of single iRBCs, suggesting their limited adhesion potential in blood flow. The main reason for poor margination of rosettes is the deformability and dynamics of rosette clusters formed by several hRBCs around one iRBC. Simulation predictions are confirmed by microfluidic experiments. Our results suggest that the main function of rosette formation is not to enhance cytoadhesion to the endothelium, but to keep the iRBCs in the blood flow, at least along straight vessel segments.

Intelligent soft matter stands at the intersection of materials science, physics, and cognitive science, promising to change how we design and interact with materials. This transformative field seeks to create materials that possess life-like capabilities, such as perception, learning, memory, and adaptive behavior. Unlike traditional materials, which typically perform static or predefined functions, intelligent soft matter dynamically interacts with its environment. It integrates multiple sensory inputs, retains experiences, and makes decisions to optimize its responses. Inspired by biological systems, these materials intend to leverage the inherent properties of soft matter: flexibility, self-evolving, and responsiveness to perform functions that mimic cognitive processes. By synthesizing current research trends and projecting their evolution, we present a forward-looking perspective on how intelligent soft matter could be constructed, with the aim of inspiring innovations in fields such as biomedical devices, adaptive robotics, and beyond. We highlight new pathways for integrating design of sensing, memory and action with internal low-power operations and discuss challenges for practical implementation of materials with "intelligent behavior". These approaches outline a path towards to more robust, versatile and scalable materials that can potentially act, compute, and "think" by their inherent intrinsic material behaviour beyond traditional smart technologies relying on external control.

Microorganisms can sense their environment and adapt their movement accordingly, which gives rise to a multitude of collective phenomena, including active turbulence and bioconvection. In fluid environments, collective self-organization is governed by hydrodynamic interactions. By large-scale mesoscale hydrodynamics simulations, we study the collective motion of polar microswimmers, which align their propulsion direction by hydrodynamic steering with that of their neighbors. The simulations of the employed squirmer model reveal a distinct dependence on the type of microswimmer-puller or pusher-flow field. No global polar alignment emerges in both cases. Instead, the collective motion of pushers is characterized by active turbulence, with nearly homogeneous density and a Gaussian velocity distribution; strong self-steering enhances the local coherent movement of microswimmers and leads to local fluid-flow speeds much larger than the individual swim speed. Pullers exhibit a strong tendency for clustering and display velocity and vorticity distributions with fat exponential tails; their dynamics is chaotic, with a temporal appearance of vortex rings and fluid jets. Our results show that the collective behavior of autonomously steering microswimmers displays a rich variety of dynamic self-organized structures. Our results imply guidelines for the design of microrobotic systems.

Self-propelled particles that are subject to noise are a well-established generic model system for active matter. A homogeneous alignment field can be used to orient the direction of the self-propulsion velocity and to model systems like phoretic Janus particles with a magnetic dipole moment or magnetotactic bacteria in an external magnetic field. Computer simulations are used to predict the phase behavior and dynamics of self-propelled Brownian particles in a homogeneous alignment field in two dimensions. Phase boundaries of the gas-liquid coexistence region are calculated for various Péclet numbers, particle densities, and alignment field strengths. Critical points and exponents are calculated and, in agreement with previous simulations, do not seem to belong to the universality class of the 2D Ising model. Finally, the dynamics of spinodal decomposition for quenching the system from the one-phase to the two-phase coexistence region by increasing the Péclet number is characterized. Our results may help to identify parameters for optimal transport of active matter in complex environments.

The huge variety of microorganisms motivates fundamental studies of their behaviour with the possibility to construct artificial mimics. A prominent example is the Escherichia coli bacterium, which employs several helical flagella to exhibit a motility pattern that alternates between run (directional swimming) and tumble (change in swimming direction) phases. We establish a detailed E. coli model, coupled to fluid flow described by the dissipative particle dynamics method, and investigate its run-and-tumble behaviour. Different E. coli characteristics, including body geometry, flagella bending rigidity, the number of flagella and their arrangement at the body, are considered. Experiments are also performed to directly compare with the model. Interestingly, in both simulations and experiments, the swimming velocity is nearly independent of the number of flagella. The rigidity of a hook (the short part of a flagellum that connects it directly to the motor), polymorphic transformation (spontaneous change in flagella helicity) of flagella and their arrangement at the body surface strongly influence the run-and-tumble behaviour. Mesoscale hydrodynamics simulations with the developed model help us better understand physical mechanisms that govern E. coli dynamics, yielding the run-and-tumble behaviour that compares well with experimental observations. This model can further be used to explore the behaviour of E. coli and other peritrichous bacteria in more complex realistic environments.

African trypanosomiasis, or sleeping sickness, is a life-threatening disease caused by the protozoan parasite Trypanosoma brucei. The bloodstream form of T. brucei has a slender body with a relatively long active flagellum, which makes it an excellent swimmer. We develop a realistic trypanosome model and perform mesoscale hydrodynamic simulations to study the importance of various mechanical characteristics for trypanosome swimming behavior. The membrane of the cell body is represented by an elastic triangulated network, while the attached flagellum consists of four interconnected running-in-parallel filaments with an active travelling bending wave, which permits a good control of the flagellum beating plane. Our simulation results are validated against experimental observations, and highlight the crucial role of body elasticity, non-uniform actuation along the flagellum length, and the orientation of flagellum-beating plane with respect to the body surface for trypanosome locomotion. These results offer a framework for exploring parasite behavior in complex environments.

Activity and autonomous motion are fundamental aspects of many living and engineering systems. Here, the scale of biological agents covers a wide range, from nanomotors, cytoskeleton, and cells, to insects, fish, birds, and people. Inspired by biological active systems, various types of autonomous synthetic nano- and micromachines have been designed, which provide the basis for multifunctional, highly responsive, intelligent active materials. A major challenge for understanding and designing active matter is their inherent non-equilibrium nature due to persistent energy consumption, which invalidates equilibrium concepts such as free energy, detailed balance, and time-reversal symmetry. Furthermore, interactions in ensembles of active agents are often non-additive and non-reciprocal. An important aspect of biological agents is their ability to sense the environment, process this information, and adjust their motion accordingly. It is an important goal for the engineering of micro-robotic systems to achieve similar functionality. Many fundamental properties of motile active matter are by now reasonably well understood and under control. Thus, the ground is now prepared for the study of physical aspects and mechanisms of motion in complex environments, the behavior of systems with new physical features like chirality, the development of novel micromachines and microbots, the emergent collective behavior and swarming of intelligent self-propelled particles, and particular features of microbial systems. The vast complexity of phenomena and mechanisms involved in the self-organization and dynamics of motile active matter poses major challenges, which can only be addressed by a truly interdisciplinary effort involving scientists from biology, chemistry, ecology, engineering, mathematics, and physics. The 2025 motile active matter roadmap of Journal of Physics: Condensed Matter reviews the current state of the art of the field and provides guidance for further progress in this fascinating research area.

Swarmalators - entities that combine swarming with synchronization - offer a powerful framework for understanding systems where spatial organization and internal degrees of freedom are bidirectionally coupled. Such interplay arises in diverse natural and engineered systems, from Japanese tree frogs and magnetic domain walls to robotic swarms. In contrast to an established theoretical framework, experimental realizations with tunable coupling between motion and phase remain elusive. Here, we present a controllable swarmalator system based on feedback-controlled self-propelling colloidal particles orbiting around reference points and interacting via hydrodynamic flows. We show that synchronization and spatial dynamics co-evolve, giving rise to collective states including synchronized clusters, rotating aggregates, and dispersive phases using a single control parameter. A rapid change of this parameter between regimes of attractive and repulsive phase-mediated interactions yields dynamic regimes inaccessible to systems with static interactions. Simulations incorporating squirmer and lubrication forces support our findings. We also find a new interaction channel through synchronization-dependent forces perpendicular to the connection axis between swarmalators. In general, our platform provides a versatile testbed for probing swarmalator physics but also offers novel strategies for the design of self-organizing active matter.

We present HTMPC, a Heavily Templated C++ library for large-scale simulations implementing multi-particle collision dynamics (MPC), a particle-based mesoscale hydrodynamic simulation method. The implementation is plugin-based, and designed for distributed computing over an arbitrary number of MPI ranks. By abstracting the hardware-dependent parts of the implementation, we provide an identical application-code base for various architectures, currently supporting CPUs and CUDA-capable GPUs. We have examined the code for a system of more than a trillion MPC particles distributed over a few thousand MPI ranks (GPUs), demonstrating the scalability of the implementation and its applicability to large-scale hydrodynamic simulations. As showcases, we examine passive and active suspension of colloids, which confirms the extensibility and versatility of our plugin-based implementation.

Translocation across barriers and through constrictions is a mechanism that is often used in vivo for transporting material between compartments. A specific example is apicomplexan parasites invading host cells through the tight junction that acts as a pore, and a similar barrier crossing is involved in drug delivery using lipid vesicles penetrating intact skin. Here, we use triangulated membranes and energy minimization to study the translocation of vesicles through pores with fixed radii. The vesicles bind to a lipid bilayer spanning the pore, the adhesion-energy gain drives the translocation, and the vesicle deformation induces an energy barrier. In addition, the deformation-energy cost for deforming the pore-spanning membrane hinders the translocation. Increasing the bending rigidity of the pore-spanning membrane and decreasing the pore size both increase the barrier height and shift the maximum to smaller fractions of translocated vesicle membrane. We compare the translocation of initially spherical vesicles with fixed membrane area and freely adjustable volume to that of initially prolate vesicles with fixed membrane area and volume. In the latter case, translocation can be entirely suppressed. Our predictions may help rationalize the invasion of apicomplexan parasites into host cells and design measures to combat the diseases they transmit.

The pursuit-evasion game is studied for two adversarial active agents, modelled as a deterministic self-steering pursuer and a stochastic, cognitive evader. The pursuer chases the evader by reorienting its propulsion direction with limited maneuverability, while the evader escapes by executing sharp, unpredictable turns, whose timing and direction the pursuer cannot anticipate. To make the target responsive and agile when the threat level is high, the tumbling frequency is set to increase with decreasing distance from the pursuer; furthermore, the range of preferred tumbling directions is varied. Numerical simulations of such a pursuit-target pair in two spatial dimensions reveal two important scenarios. For dominant pursuers, the evader is compelled to adopt a high-risk strategy that allows the pursuer to approach closely before the evader executes a potentially game-changing backward maneuver to pull away from the pursuer. Otherwise, a strategy where the evader tumbles forward with continuous slight adjustments of the propulsion direction can significantly increase the capture time by preventing the pursuer from aligning with the target propulsion direction, while maintaining the persistence of the target motion. Our results can guide the design of bioinspired robotic systems with efficient evasion capabilities.