Self-Organizing and Evolving Active Matter

We present an experimental framework for studying social learning in swarm robotics, utilizing Pogobots — an open-source, open-hardware platform specifically designed for research in collective autonomous systems. Exploiting Pogobots’ built-in photosensors, infrared communication, and vibration-based actuation, we implement a fully decentralized, online, end-to-end learning algorithm that enables the swarm to acquire a phototaxis behavior. Beyond demonstrating task acquisition, we analyze the parameters' dynamics of the learning process, characterizing the emergence of collective behavior. Our results highlight the potential of socially distributed learning mechanisms in minimal robotic platforms and contribute to the understanding of self-organization in biologically relevant active matter systems.

We consider a lattice model of pulsating particles that organize into dynamical patterns stirred by topological defects. These patterns capture the complex phenomenology of deformable particles with pulsating sizes [1-4] reminiscent of contraction waves in some biological systems (e.g., cardiac tissues [5]). We rationalize the emergence of such waves from the broken rotational invariance of hydrodynamic equations, and study the corresponding entropy production rate (EPR). We demonstrate that the EPR evaluated at the hydrodynamic level coincides with that of the particle-based lattice dynamics, and argue that this exact correspondence stems from the thermodynamically consistent mapping of our lattice dynamics into a specific class of non-ideal reaction-diffusion systems. By examining how dynamical patterns affect the local and global profiles of EPR, we relate the dissipation of the system with its emergent topology. [1] Y. Zhang and É. Fodor, Phys. Rev. Lett. 131, 238302 (2024) [2] W. D. Pineros and É. Fodor, Phys. Rev. Lett. 134, 038301 (2025) [3] T. Banerjee, T. Desaleux, J. Ranft, and É. Fodor, arXiv:2407.19955 [4] A. Manacorda and É. Fodor, Phys. Rev. E 111, L053401 (2025) [5] A. Karma, Annu. Rev. Condens. Matter Phys. 4, 313 (2013)

Enzymatic nanomotors self-propel by converting free molecular energy from chemical reactions. While these systems have primarily been studied and applied as individual particles, they hold significant potential when implemented as collective swarms. Recently, the collective motion of nanomotors has garnered interest due to their expanded area of influence, enhanced effects at target sites, and unique motion dynamics observed only in large populations. However, studies on nanomotor swarms have been largely restricted to 2D, providing limited insights into their overall 3D behavior. Additionally, the combination of properties such as magnetic navigation and enzyme-powered motion remains underexplored, despite its potential to enable reconfigurable and adaptable collective dynamics controlled on demand. In this study, we introduce urease-powered nanomotors based on bioproduced magnetosomes that can be (i) magnetically guided as a nanomotor ensemble to a target area and (ii) catalytically expand the swarm to enhance the area explored at the air-water interface. We first investigate this catalytic collective phenomenon under varying conditions, including particle and substrate concentrations and media viscosity. Special attention is given to often-overlooked aspects of collective active matter, such as analyzing motion from both top and side views to assess 3D behavior indirectly and the role of fluid dynamics caused by inactive nanoparticles in urea. Finally, we examine swarm behavior under a magnetic gradient field to steer the swarm toward a target area and catalytically trigger its expansion in open settings. This multimodal strategy is then exploited in confined environments with turns to demonstrate the increased concentration of magneto-enzymatic swarms to the target area. This approach fosters reconfigurable nanomotor swarms for implementations requiring precise localization and maximum agent concentration in inaccessible areas, particularly for applications targeting the air-water interface, such as environmental remediation of oil spills and bacteria accumulations.

Olga Bantysh1,2, Francesc Sagués Mestre1,2, Jordi Ignés-Mullol1,2 1 Departament de Química Física, Universitat de Barcelona, Barcelona, Spain 2 Institute of Nanoscience and Nanotechnology, Universitat de Barcelona, Barcelona, Spain We assemble a biomimetic active material from microscopic components like cells' filaments and protein motors that consume energy and generate continuous motion. Such active systems are capable of self-organization at different length and time scales, often exhibiting turbulent flows and the emergence of long-range orientational order, which is a characteristic of active nematics (AN). Previously, it was demonstrated that, by bringing into contact a two-dimensional AN with an anisotropic oil that features smectic liquid-crystalline order, it is possible to transform the originally turbulent flow of the active fluid into well-aligned flows ordered by a magnetic field [1]. Alternatively, the flow of active nematic could be controlled by confining walls [2] or arrangements of obstacles [3]. In present work we combine both approaches: well-aligned flows of AN ordered by a magnetic field were confined between walls of PDMS channels. The resulting quasi-laminar flows of AN are perturbed by closely located channel walls and reorganized in arrays of vortexes forming a hexagonal lattice. The emergence of antiferromagnetic vortex lattices is correlated with positional ordering of topological defects and the appearance of density patterns. The observed self-organization of the active flows is activity dependent and reflects the inherent properties of the aligned AN. The described system is an example of pattern formation from instabilities of AN flows and suggests potential applications in the design and control of active materials. Keywords: active nematics, antiferromagnetic vortex lattice, self-organization. Acknowledgements: All authors are acknowledge funding from PID2022-137713NB-C21. The presenting author also acknowledges funding from Joan Oró 2023_FI-1_00123. References [1] P. Guillamat, J. Ignés-Mullol and F. Sagués, Proc. Natl. Acad. Sci. U. S. A., 2016, 113, 20. [2] J.Hardoüin, J. Laurent, T. Lopez-Leon, J. Ignés-Mullol and F. Sagués, Soft Matter, 2020, 16. [3] B. Zhang, B. Hilton, C. Short, A. Souslov and A. Snezhko, Phys. Rev. Research, 2020, 2, 043225.

It is known from literature that certain swimming microorganisms, such as the unicellular alga Chlamydomonas reinhardtii (CR), collectively form bioconvection that can be observed as regular patterns in cell concentration [1]. Bioconvection is caused by the swimming behavior of individual cells that is biased by their responses to environmental stimuli. Bioconvection of CR is caused by the tendency of the cells to align themselves against gravity (negative gravitaxis), which causes cells to accumulate near surface despite being denser than the surrounding liquid, and the tendency to swim towards downwelling flow (gyrotaxis), which causes the cells to sink in plumes [1]. In addition, CR can sense light and swim towards or away from it (positive or negative phototaxis) [2]. Recently, it has been shown that metabolic activity, which depends on light intensity in an anaerobic environment, changes cell motility and controls the emergence of bioconvection [3]. In this work, we investigated the behavior of CR (strain CC125) in biocompatible ferrofluids which can yield additional ability to control bioconvection with magnetic fields, in addition to light and gravity. Previously, it has been shown that swimming directions and active turbulence of bacteria can be controlled using external magnetic field [4]. Here we expand the approach to microalgae and bioconvection. We compared pattern formation without ferrofluid and with different ferrofluid concentrations. We discovered that bioconvection formed in low concentration of ferrofluid, whereas higher ferrofluid concentration delayed and prevented plume formation. Ferrofluid impacts the environmental stimuli experienced by CR: ferrofluid has a higher density than culture medium, which impacts gravitactic reorientation of CR, and it absorbs light, which impacts phototaxis and metabolic activity of CR. When magnetic field was applied, the force exerted by the ferrofluid on the cells acted opposite to gravity and suppressed bioconvection. Our results show that magnetic field provides an accessible method to control the fundamental mechanisms behind bioconvection, possibly extending applications of bioconvection in biotechnology. References 1. M. A. Bees, Advances in Bioconvection, 2020, Annu. Rev. Fluid. Mech., vol. 52, pp. 449-476. 2. K. W. Foster & R. D. Smyth, Light Antennas in Phototactic Algae, 1980, Microbiological reviews, vol. 44, no. 4, pp. 572-630. 3. A.A. Fragkopoulos, F. Böhme, N. Drewes, & O. Bäumchen, Metabolic activity controls the emergence of coherent flows in microbial suspensions, 2025, Proc. Natl. Acad. Sci. U.S.A., vol. 122, no. 4. 4. K. Beppu & J. V. I Timonen, Magnetically controlled bacterial turbulence, 2024, Commun. Phys., vol. 216, no. 7.

Many complex systems feature a specific scale separation: larger groups of interacting agents or units of interest are considered with emerging meso- or macroscalic behaviour being of interest whereas the internal mechanations on smaller scales are likely inaccessible, but definitely intractable. The generalized (often phenomenological) dynamics on the new smallest scales (size or interaction range of the agents, interaction times) are not subject to the same constraints as microscopic equations of motion. In particular, the Newtonian axioms and conservation laws of standard mechanics are no longer valid: stored energy can be used to drive the system out-of-equilibrium (broken detailed balance), interactions can be non-reciprocal. We extend kinetic theory, an approach to statistical physics that is rooted in systematically starting from equations of motion, to such generalized dynamics. We derive the Boltzmann- and Landau-equations the essential mesoscalic dynamic equations beyond the pervasive mean-field (in various contexts also known under the names Vlasov, Debye-Hückel or Hartree) approximation. The technical basis of this is using the assumption of one-sided molecular chaos to close the BBGKY hierarchy equations and track correlations during interactions. The specific system we show display for is composed of active, self-propelled particles with short-ranged alignment interactions. We show that mean-field theory is unphysical and qualitatively wrong. We show results for systems with non-reciprocal couplings and discuss the importance of the two important conservation laws in this system: a hidden conservation law with respect to the orientational variables and non-trivial issues with respect to probability conservation in perturbative theories. References: Boltz, H.-H., Kohler, B., & Ihle, T. (2024). Entropy, 26(12), 1054 Kürsten, R., Mihatsch, J., & Ihle, T. (2025). Phys. Rev. E 111, L023402 Ihle, T., Kürsten, R., & Lindner, B. (2023). arXiv:2303.03357 [cond-mat.stat-mech]

In a vast class of systems, which includes members as diverse as active colloids and bird flocks, interactions do not stem from a potential, and are in general nonreciprocal. Thus, it is not possible to define a conventional energy function, nor to use analytical or numerical tools that rely on it. Here, we overcome these limitations by constructing a Hamiltonian that includes auxiliary degrees of freedom; when subject to a constraint, this Hamiltonian yields the original non-reciprocal dynamics. We show that Glauber dynamics based on the constrained Hamiltonian reproduces the steady states of the original Langevin dynamics, as we explicitly illustrate for dissipative XY spins with vision-cone interactions. Further, the symplectic structure inherent to our construction allows us to apply the well-developed notions of Hamiltonian engineering, which we demonstrate by varying the amplitude of a periodic drive to tune the spin interactions between those of a square and a chain lattice geometry. Overall, our framework for generic nonreciprocal pairwise interactions paves the way for bringing to bear the full conceptual and methodological power of conventional statistical mechanics and Hamiltonian dynamics to nonreciprocal systems.

Colloids that generate chemicals, or “chemically active colloids”, can interact with their neighbors via forces arising from such chemical gradients. These chemically active colloids are useful for constructing functional materials with tunable electrical, optical, and mechanical properties. Understanding and controlling their pairwise interactions and the resulting self-assembled superstructure is key to these applications, but an overarching conceptual framework to consolidate and explain the experimental results scattered throughout the literature is yet to be established. Here, we present such a framework based on the principle of ionic diffusiophoresis and diffusioosmosis, by combining experiments, theories, Brownian dynamic simulations and finite element simulations. Specifically, this framework predicts that, depending on the relative diffusivity of the released cations and anions, and the relative zeta potential between a colloidal particle and the flat surface it resides on, a chemically active colloid interacts with its neighbors through short-range and long-range interactions that can both be either repulsive or attractive, yielding four possible scenarios. These pairwise interactions then give rise to four different types of colloidal assemblies of varying dispersity and connectivity. These predictions are in quantitative agreement with both numerical simulations and with experiments performed in our own laboratory as well as those reported in the literature. Our results represent a solid step toward building a complete theory for understanding and controlling chemically active colloids, from the molecular level to their mesoscopic superstructures and ultimately to the macroscopic properties of the assembled materials.

Many different collective dynamics emerge from self-alignment, such as collective actuation in active solids and collective migration of motile agents. However, since self-aligning torque couples rotations and displacements at an individual level, interesting dynamics arise in self-aligning active particles even in the absence of interparticle interactions. Here we study experimentally (by using self-propelled robots), numerically, and theoretically the emergent angular dynamics in a single chiral active particle when translational forcing is imposed on it at different constant velocities. Decreasing the imposed speed, at the zero-noise limit the system exhibits a depinning transition when the alignment torque is no longer able to balance the chirality of the particle, moving from a zero mean angular velocity steady state to a rotational steady state. In the regime where there is no depinning, we observe a sort of rotational rectification effect due to fluctuations induced by angular noise, for which we calculate the mean first-passage time. Finally, from the Fokker-Planck equation we analytically obtained the stationary probability distribution for the particle orientation angle, which verifies our previous findings.

The target search problem is of fundamental importance in various domains, ranging from biology to robotics, where efficient navigation in complex environments is crucial. In this work, we investigate the efficiency of intermittent search strategies employed by active Brownian particles navigating through viscoelastic media, such as mucus, polymer solutions, and biological tissues, which exhibit both viscous and elastic characteristics. To this end, we employ projective simulation, a reinforcement learning framework particularly suited for problems with sparse rewards, as is typical in target search scenarios. The dynamics of the particles are modeled by a generalized Langevin equation that incorporates memory effects via a fractional time derivative. This fractional derivative is controlled by a parameter $\beta$, which allows for continuous tuning of the medium’s mechanical response, from purely elastic behavior ($\beta = 0$) to purely viscous behavior ($\beta = 1$). By discretizing this equation of motion, we simulate particle trajectories under various viscoelastic conditions, enabling a systematic exploration of how medium properties influence search performance and learning efficiency.

While in conventional fluids viscosity solely expresses dissipation, the interest in viscous responses beyond dissipation has grown greatly in recent years. Indeed, under broken parity or time reversal symmetry, fluids can exhibit an antisymmetric, non-dissipative, viscous contribution – the odd viscosity. Until now, the majority of the works devoted to odd fluids have focused on bulk properties or interfacial problems that ignore surface tension. It is known that odd plasmas host non-reciprocal and non-linear modes [1], but boundary dynamics remain less studied. In this talk, we explore the behaviour of surface waves dominated by the interplay of odd viscosity and surface tension in a deep water limit. Such waves have the chirality defined by the odd viscosity, thus breaking reciprocity. In addition, we find that the nature of the right and left propagating modes is strikingly disparate, with one being increasingly dispersive while the other approaches an acoustic limit [2]. Our analytical results are backed and complemented by direct numerical simulation of incompressible Navier–Stokes. With it, we study the surface perturbations past the linear regime and explore the emergent nonlinear effects on both the boundary and bulk flow. Lastly, we will discuss a nonlinear and nonlocal scalar model, akin to a high-order Benjamin–Ono equation, that captures the overall behaviour of the surface perturbations. Bridging the framework of non-reciprocity to hydrodynamics through odd viscosity not only progresses our theoretical understanding of fluids under parity breaking but also opens the venue to selective and controllable systems, in envisioned future applications that range from microfluidics to industrial piping. [1] P. Cosme, H. Terças, Phys. Rev. B 107, 195432, 2023 [2] M. Jalaal et al., in preparation.

Microorganisms often face strong confinement and hydrodynamic flows while navigating their complex habitats, such as biological tissues and gels and environmental soils and sediments. Combining finite-element methods and stochastic simulations, we study the interplay of active transport and heterogeneous flows in dense porous channels. Our results demonstrate that swimming always slows down the traverse of agents across the channel, which manifests in robust power-law tails of their exit-time distributions for comparable swim speed and flow strength. Our results can be collapsed into a master curve for various packing fractions and swim speeds and reveal a scaling exponent of $\approx 3/2$. We rationalize this by identifying a motility pattern where agents alternate between surfing along fast streams and extended trapping phases, determining the power-law exponent. Strikingly, trapping occurs not only at obstacle boundaries but also significantly in the flow backbone due to shear-induced reorientation in the highly heterogeneous fluid environment. These findings provide key insights into the onset of biofilm clogging and guide the design of novel microrobots capable of operating in complex, porous media.

Quincke rotation occurs when a dielectric particle in a weakly conducting fluid rotates spontaneously in response to an external DC electric field \textbf{E}. Above a threshold value \textbf{E}$_c$, surface friction drives rolling in the plane orthogonal to \textbf{E}, at a constant speed set by the field. Although single rollers typically perform quasi-linear random walks, emergent collective motion in sufficiently dense colloidal suspensions lead to the formation of vortexes, density bands, directed flows etc, subject to the geometry of the confining region. In our system, we introduce an additional degree of freedom using superparamagnetic colloids and observe markedly different dynamics. With no magnetic field \textbf{B}, rollers execute tight circular trajectories or even orbits. These are more unstable at higher \textbf{E} fields, as periods of circular motion may be interspersed with short “walks”. Introducing a homogeneous in-plane \textbf{B} alongside the electric field linearises the circular motion, as the rollers’ induced magnetic moment aligns with \textbf{B}, thereby fixing the Quincke rotation axis. Coherent linear trajectories perpendicular to the magnetic field lines are executed, which is consistent with other work. However, as we increase the applied magnetic field beyond 20 mT, we see the appearance of an anomalous linear mode of active rollers travelling parallel to the magnetic field axis. In numerical simulations, we have implemented a model of anisotropic magnetic susceptibility to account for the stabilisation of the magnetic moment, thereby facilitating the emergence of this secondary linear mode. Our simulations show the magnetic moment precessing the angular velocity, in the plane orthogonal to the rolling surface, as the roller successfully replicates the trajectories colinear with \textbf{B} observed in experiments for a range of initial conditions. We have consolidated our proposed stabilising mechanism with a simple analytic model which identifies a set of secondary energetic minima corresponding to the tumbling mode seen in simulations.

We study the hydrodynamic interactions of swimming microorganisms with nearby deformable bound- aries omnipresent in their natural habitats. The boundary, characterized by its surface tension and bending rigidity, is deformed by the flow produced by the microswimmer and thereby modifies its swimming veloc- ities. Describing the far-field flow of the agent as a combination of a force and torque dipole, we compute small instantaneous deformations of the boundary. We further use the Lorentz reciprocal theorem to obtain leading-order corrections of its swimming velocities and compute a phase diagram based on the swimmer’s initial orientation and the material properties of the deformable boundary. Our results reveal that pushers can both re-orient away from the boundary, leading to overall hydroelastic scattering, or become trapped near the boundary, while pullers exhibit enhanced trapping. These findings demonstrate that the complex hydroelastic interactions can generate behaviors that are fundamentally different to swimming near planar walls. Ref: S. Garai, et. al., arXiv preprint arXiv:2502.02462

Living beings often thrive in groups - from birds to bacteria. Ordered groups are formed when organisms interact locally with their neighbours, such as, force due to displacement of water by fish (hydrodynamics), chemical exchange between bacteria, and visual perception of neighbours by birds. But how do local interactions lead to the emergence of global order in self-organised groups, especially in microscopic systems? Here, we present a collective system made of magnetic microdisks. We design and control the balances of local interaction forces between the microdisks so that distinct globally ordered collective behaviours emerge. We study the effect of heterogeneity and non-reciprocal interactions on the collective behaviours of the disks. Some of the behaviours of the disks resemble crystals of starfish embryos. Overall, this talk highlights our system's capability to act as an adaptable and versatile model system for studying collective behaviours and for development of versatile microrobot collectives.

Microtubule (MT)-based active matter is a soft biomaterial generating mesoscale chaotic flows that is sustained at a steady-state by energy consumption. Here, I introduce the disordered protein Tau as a novel component of MT-based active matter. Tau naturally binds and stabilizes MT filaments in vivo and undergoes liquid-liquid phase separation in vitro, forming distinct condensates. When introduced into MT-based active gels, Tau condensates initially recruit MTs from their environment, generating localized contractile flows. Upon reaching a critical MT density within the condensates, they dissolve, triggering a striking contractile-to-extensile flow transition. This phenomenon can be precisely modulated by varying energy availability (ATP concentration) or mechanical constraints (MT concentration). My findings highlight a unique interplay between mechanical activity and protein phase separation, offering new strategies to design active matter systems with programmable and tunable flow behaviors.

Dense bacterial suspensions exhibit collective behavior similar to inertial turbulence, despite cells swimming at an effective zero Reynolds number. This phenomenon is called active turbulence. By employing photokinetic Escherichia coli bacteria, we investigate the phenomenon's response to temporal variations in activity. By removing activity from the sample, we induce a transition from an active state, in which the bacteria are motile, to a passive state, in which they can instead be considered as thermal colloids. Conversely, reintroducing activity induces a transition to the active state. We find that "awakening" occurs on a characteristic time scale that is set by the waiting time. Furthermore, we show that the reawakened turbulent pattern can be strongly correlated with the past flow prior to light removal. This memory is found only for densities higher than the critical value for the onset of turbulence.

Biological particles feature many tactic behaviours, exploiting every possible feature of their environment to generate motion. Using light to phototax, using chemicals to chemotax, even gravity can help guide biological particles. Artificial swimmers are being designed to mimic these biological processes. They do this by interacting and manipulating the flow of their fuel sources whereas natural microswimmers accomplish this same process through interacting with their environmental (Nsamela 2023). In general Chlamydomonas Reinhardtii has been viewed in macro, or held still to watch its tails flail. In our work we take a close up view of C.reinhardtii and observe its swimming and navigation modes: chemo-, photo-, rheo-, gravi-taxis in action. We use novel microfluidic techniques to create precisely controlled gradients, flows and conditions to test the navigational abilities of artificial and biological entities alike. In working with algae we compare and contrast to artificial active particles and marvel at the extent of their biomimicry potential.

Nonreciprocal interactions and conservation laws play a crucial role for self-organisation processes in active matter [1]. Even at the level of minimal field theories like nonreciprocal Cahn-Hilliard models [2], many aspects of pattern formation and lengthscale selection are yet unexplored. While the passive Cahn-Hilliard model exhibits uninterrupted coarsening, stable traveling waves observed in nonreciprocal Cahn-Hilliard models often exhibit finite wavelengths [3]. However, little is known on the stability of traveling states with long wavelengths, such as phase-separated states that are set in motion by weak nonreciprocal interactions. Here, we employ a minimal version of the nonreciprocal Cahn-Hilliard model and reveal several destabilizing mechanisms to ultimately show how stability is always lost at very long wavelengths. [1] A. Dinelli et al., Nat. Commun. 14, 7035 (2023); Y. Duan et al., Phys. Rev. Lett. 131, 148301 (2023). [2] S. Saha et al., Phys. Rev. X 10, 041009 (2020); Z. H. You et al., Proc. Natl. Acad. Sci. U. S. A. 117, 19767 (2020); T. Frohoff-Hülsmann et al., Phys. Rev. E 103, 042602 (2021); [3] D. Greve and U. Thiele, Chaos 34, 123134 (2024); F. Brauns and M. C. Marchetti, Phys. Rev. X 14, 021014 (2024).

Conway’s Game of Life shows that simple rules can generate a rich diversity of emerging structures. More recently, this cellular automaton has been moved to continuous space by S. Rafler (2011) in a simulation called SmoothLife. Related to its isotropic rule, the beauty of patterns generated by this continuous Game of Life has attracted the attention of a growing community at the intersection of science and computer art. We study a minimal variant of the continuous Game of Life that generates cell-like patterns capable of self-replicating, gliding and vanishing. Emerging dynamic morphologies for these cell-like patterns exhibit numerous bifurcations, instabilities and dynamical phase transition. An interpretation as a non-standard reaction-diffusion system is discussed. We show that the introduction of a conservation law for available and consumed resource can let the system self-organise at criticality, between a dense volume-limited regime and a dilute resource-limited regime. We further extend the model to allow individual variations of the parameters and stochastic mutations. Ameboid motion appears as one of the steady states of the random walk on the critical manifold of the resulting evolutionary morphogenetic system. The reminiscence of biological cell division, motility and death, along with a concise formulation and the ease of numerical simulation, makes it a particularly appealing toy-model for the emergence of life-like patterns.

Interactions in active matter systems, both soft and biological, are generally non-reciprocal,1 and can be tailored in colloidal systems to investigate the collective effects they induce. Here, we study self-propelling dimers of Janus particles that interact via non-reciprocal torques due to induced electrical dipoles, expanding previous work on non-reciprocal monomers.2,3 Experiments show these dimers forming polar streams or rivers, elongated regions with high particle density and orientational alignment along the extent of the stream. This distinguishes them from traveling bands observed in classical models of flocking, where particles are oriented perpendicularly to the band. To analyze and understand the emergence of this phase, we perform Brownian dynamics simulations paired with analytical coarse-graining methods. With these analyses, we will test the hypothesis that polar streams emerge from the combination of two paradigmatic transitions in active matter: motility-induced phase separation and flocking.

Active suspensions of microswimmers, such as bacteria swimming in a solvent, exhibit unique and anomalous properties absent in passive systems. While numerous simulation studies have focused on pusher-type swimmers, such as E. coli and Bacillus subtilis, which generate extensile flow fields, investigations of puller-type swimmers, like Chlamydomonas reinhardtii, remain relatively limited. In this study, we perform direct hydrodynamic simulations using model swimmers designed to mimic Chlamydomonas reinhardtii, to explore the behavior of sheared suspensions of puller-type microswimmers. These swimmers generate contractile flow fields along their swimming directions, leading to hydrodynamic interactions that preferentially align them vertically. Our simulations reveal that this alignment and the resulting orientational order are particularly pronounced near boundary walls, where local swimmer density is enhanced. This near-wall effect plays a dominant role in determining the overall swimming dynamics and rheological properties of the suspension. Furthermore, our model suspensions exhibit a significant confinement effect. As the channel height decreases, we observe a reversal in swimming direction and a crossover from viscosity enhancement to viscosity reduction. This behavior is governed by the interplay between the confinement scale and the intrinsic trajectory radius of the swimmers under shear flow. These findings demonstrate that puller-type microswimmers exhibit anomalous rheological and collective behaviors that not only set them apart from passive systems, but also from their pusher-type counterparts.

Active particles are autonomous agents that exhibit self-propelled motion. When agitated by external cues or stimuli from ambient environments, they reorient themselves along vector fields or gradients of scalar fields relying directly on the laws of physics. In this talk, we first discuss a new class of the orientational behavior of an active agent in chiral active fluids, which are characterized by parity symmetry violation [1]. We rigorously demonstrate that a force dipole moment, or stresslet---a leading contribution to the flow induced by swimming microorganisms and synthetic particles (e.g., a Janus particle)---leads to a chirotactic response of suspended particles. Due to chirotaxis, swimmers now align either along or perpendicular to the axis of chirality in fluids. The mechanism would provide a new tactic mechanism explaining locomotion of microorganisms and open up a novel strategy for controlling microparticles via an external chirality measure. Finally, we talk about a continuum theory that accounts for fluidic or solid environments composed of active constituents. [1] Chirotactic response of microswimmers in fluids with odd viscosity, Y. Hosaka, M. Chatzittofi, R. Golestanian, and A. Vilfan, Phys. Rev. Research 6, L032044 (2024).

Bacteria are microorganisms that achieve motility by rotating helical appendages called flagella. The model bacterium \textit{E. coli} travels through aqueous solutions using run-tumble motility, consisting of straight trajectory segments of approximately constant speed and brief random reorientation events. Chemotaxis, i.e. biased motion relative to chemical gradients, is achieved by modulating the frequency of tumble events in response to chemosensory input, such that up-gradient runs are longer than down-gradient ones on average. Hydrodynamic surface interactions lead to attraction of swimming \textit{E. coli} to surfaces as well as swimming in circles at surfaces. Escape from a surface is typically driven by a tumble. The difference in surface interactions between the run and tumble states raises the question of how chemotaxis - which relies on the modulation of these states - is impacted by the presence of surfaces. We perform high-throughput 3D bacterial tracking in chemical gradients in microfluidic chambers to address this question. Based on the analysis of large datasets spanning $>10^4$ cells, we discover dramatic heterogeneity between individuals in chemotactic performance which correlates with average run speed. The population-averaged performance, measured as the average drift velocity in the gradient direction, is dominated by a fast-swimming minority of the population. Moreover, slower swimming cells show an average drift in the opposite direction. We analyze statistics of individual 3D trajectories to identify the underlying mechanisms.

Hydrodynamic interactions are essential in governing the collective dynamics of particles, often giving rise to striking self-organized structures. In this study, we explore the collective behavior of spinner monolayers in viscoelastic fluids through fully resolved direct numerical simulations, capturing the intricate hydrodynamic coupling between the particles and the surrounding medium. Our simulations reveal a previously unreported instability unique to viscoelastic environments: an initially uniform monolayer spontaneously evolves into rotating, particle-rich clusters separated by voids. This emergent phase separation stems from attractive hydrodynamic interactions mediated by the Weissenberg effect. Specifically, the rotational motion of the spinners generates normal stress differences in the viscoelastic medium, leading to hoop stresses that drive upward and downward flows around the upper and lower hemispheres of each spinner. These flows produce a divergent field that promotes interparticle attraction, ultimately triggering the clustering and phase separation. These findings shed light on the interplay between viscoelasticity and particle dynamics, offering new avenues for controlling self-organization in complex fluid environments.

Authors Andrea Lama (1,2) Prof. Mario Di Bernardo (1,2) Prof. Sabine H.L. Klapp (3) (1) Scuola Superiore Meridionale, Naples, Italy (2) University of Naples Federico II (3) Technical University of Berlin ------ Abstract --------------- Field theories for complex systems traditionally focus on collective behaviours emerging from simple, reciprocal pairwise interaction rules. However, in many natural and artificial systems, agents are capable of performing real-time decisions based on, e.g., some control goal. Examples range from animal groups coordinating their actions to swarms of robots performing distributed control tasks. The microscopic decision-making process, which critically shapes the emerging collective behaviours, can introduce both nonreciprocity and many-body interactions, challenging conventional field-theoretic approaches. We develop a theoretical framework to incorporate decision-making into field theories using the shepherding control problem as a paradigmatic example of a multi-agent control system, where agents (herders) must coordinate to confine another group of agents (targets) within a prescribed goal region. By continuously approximating two key decision-making processes of the herders- target selection and trajectory planning - we derive field equations featuring a novel nonreciprocal coupling in the herders’ density dynamics. This coupling encodes the goal-oriented speed of the herders at the continuum level and allows us to observe the emergence of an inhomogeneous steady state where the density field of the herders confines that of the targets, capturing the essential feature of this distributed control problem. Our theory can reproduce different behaviours beyond confinement by suitably modifying this new coupling term, offering a general framework for incorporating decision-making into continuum models of collective behaviour, with applications ranging from swarm robotics to crowd management systems.

Bacterial chemotaxis is driven by a temporal comparison between their current and past environmental cues. This "memory" introduces inertia in the direction of the movement, thereby reducing the impact of chemical sensing noise. Chemotactic experiments are typically performed in confined environments, where bacterial diffusivity was found recently to depend on the confinement height as well as a circular kinematics at surfaces caused by hydrodynamic interactions. Escaping from the surface requires a tumble—a brief moment of reorientation. For adapted bacteria, memory effects leading to large distributions of run-times, and consequently to large residence times at the surface, were attributed to the fluctuations of a protein (CheY-P) near the motor. Similarly, our work shows that the chemotactic flux depends on the confinement height, with no net chemotactic flux at surfaces. As a result, the chemotactic behaviour is essentially driven by motion in the bulk. However, the impact of surfaces on chemotaxis is not limited to reducing mean bacterial chemotactic behaviour alone. In fact, a correlation exists between bacterial memory time and surface residence time. When an E. coli swims toward a nutrient source and encounters a surface, it typically spends more time on the surface, effectively "remembering" that it was previously heading in the right direction. Conversely, when a bacterium moves down a gradient and encounters a surface, it rapidly tumbles and escapes. Comparisons between experimental results and numerical simulations[ suggest that the duration of the bacterial memory may vary depending on the chemical stimulus that triggers the chemotactic response.

Living systems exhibit remarkable self-organization driven by active forces interacting within viscoelastic environments, as exemplified by swimming sperm, gut bacteria dynamics, and synchronized cilia movements. Replicating these complex biological behaviors synthetically remains challenging due to the interplay between active stresses, generated by motor proteins, and passive viscoelastic responses of the surrounding environment. To address this, we assemble a minimal composite system combining microtubules (MTs) driven by kinesin motor proteins with flexible DNA polymers, forming an active-elastic gel. In isolation, MT-based active gels typically display unregulated turbulent-like flows, characterized by short-range velocity correlations (~100 um). However, upon incorporation of DNA polymers, chaotic active flows spontaneously drive polymer entanglement, resulting in the formation of a mesoscale elastic network that mediates mechanical feedback and long-range interactions. Interestingly, we observe a first-order phase transition dependent on the polymer length distribution relative to the velocity correlation scale of the active flows. Specifically, short DNA polymers produce localized chaotic flow, intermediate lengths yield large-scale vortices, and longer DNA chains induce pronounced global oscillatory dynamics, achieving correlation lengths extending up to a millimeter. Oscillation periods are found to depend on activity via molecular motor concentration and confinement geometry, and typically lasting tens of minutes. This composite system thus demonstrates tunable control over active matter dynamics, providing insights into how passive viscoelasticity can facilitate spatial and temporal synchronization in synthetic active systems.

Active nematic is a class of active matter which exhibits orientational order, e.g., bacterial suspensions, cell populations, etc. A topological defect is a singularity of the orientational field. It is a topologically protected robust structure, and plays an important role, e.g., in the process of morphogenesis. In this study, we investigate the configuration of topological defects in two-dimensional active nematics around a circular obstacle. In the case of passive liquid crystals, the defects configuration around a circular obstacle can be identified by analytical calculation based on the Coulomb interaction between defects and the method of image charge. In the case of active nematics, however, we must consider the flow field induced by the active stress. Then, to investigate how the defects configuration deviates from the passive one due to the flow field, we performed numerical simulations based on a continuum model. As a result, the configuration of defects deviates from the passive one, and the magnitude of deviation can be controlled by the strength of active stress. Our result reveals the mechanism for determining the defects configuration in active nematics and has the potential to contribute to a further understanding of the process of morphogenesis.

Faced with an epidemic, rational agents (humans or other animals) will socially distance to avoid infection and prevent the spread of the disease. To understand this self-organized behavioral response, we use optimal control and game-theory to understand (1) how the utility/cost function (e.g., the relative cost of socially distancing versus the cost of becoming infected) of the individuals determines the degree to which they socially distance, and (2) how this individual response determines the propagation of the disease in the population (i.e., indefinite suppression or herd-immunity). Finally, we also consider the inverse problem of inferring the (hidden) utility that determines the response of the individuals purely from their observed behavior. For this, we have developed a physics informed Neural Network that encodes the relevant game-theoretical constraints.

The development of an organism starting from a fertilized egg involves the self-organized formation of patterns and the generation of shape. Such morphogenetic processes often rely on flows of cells and molecules driven by molecular force generation. Here, we investigate how the shape of an organism guides such active flows and thereby the formation of chemical patterns. We study active surfaces, i.e. active processes confined to a surface of complex geometry. We focus in particular on an active fluid model of the cell cortex. With this, we find that active cortical stresses can drive a rotation of the cell that aligns the chemical pattern of the stress regulator with the geometry of the cell surface. Specifically, we find that active tension in the cytokinetic ring ensures that a cell divides along its longest axes, consistent with experimental observations in mouse and nematode embryos. Thereby the cytokinetic ring is aligned with the saddle of a prolate sphere. Notably we find that even point like sources of isotropic active tension are advected towards such saddle geometries, also in non-spherical topologies. We find that such an advection of active particles towards certain points in the intrinsic surface geometry of a fluid film is a generic consequence of viscosity. Thus, active surfaces generally exhibit a sense of their geometry, as surface geometry guides flows and thus patterns, which may contribute to the robustness of morphogenetic processes.

The celebrated theorem of Bohr and van Leeuwen guarantees that a classical charged system cannot have a magnetization in thermal equilibrium. Quantum mechanically, however, a diamagnetic response is obtained. In contrast, we show here that a classical charged active system, consisting of a motile particle confined to the surface of a sphere, has a nonzero magnetization and a paramagnetic response. We numerically sample Langevin trajectories of this system and compare with limiting analytical solutions of the Fokker-Planck equation, at small and large temperatures, to find excellent agreement in the magnetic response. Our Letter suggests experimental routes to controlling and extracting work from charged active matter.

Several chemical and biomedical applications require systematic processing of micron-sized fluid samples. To realize this, so-called microfluidic lab-on-a-chip devices with micron-sized channels are widely used. Often, one needs to manipulate two layers of immiscible fluids in such channels. The interface separating the two fluid components costs energy, which is quantified by surface tension. Thus, any deformation of a planar fluid interface increases energy. In our work, we assign one more property to the interface in the form of dipolar forces acting perpendicular to the interface. We name it the \emph{activity} of the interface, and it is achieved by covering the interface with active particles. The notion of activity is inspired by swimming microorganisms. Using computer simulations, we discover that the presence of activity affects the stability of the interface. We notice that dipolar forces pointing toward the interface counter the stabilizing effect of surface tension, so that the interface deforms. In contrast, force components pointing away stabilize the interface against perturbation. The destabilizing activity might seem undesirable at first. However, we demonstrate that one can leverage such activity-induced instability to generate microfluidic droplets. In addition, we can also control droplet formation by varying the magnitude of dipolar forces in real time, which can be accomplished using light-sensitive active particles in practice. Realizing our proposed microfluidic design will impact various real-life applications, e.g., encapsulation of biological cells for tissue engineering or for early disease diagnosis.

Tissue morphogenesis is controlled by two-dimensional patterning of gene expression in epithelial layers,that determines cell fates. The mechanisms of pattern formation involve intracellular regulatory networks controlled by paracrine and autocrine signaling. We develop a general logical scheme to deduce the morphology of two-dimensional patterns in the field of morphogene gradients

Microscale swimmers, such as bacteria and algae, exhibit characteristic collective behaviors. However, precise control over their experimental conditions remains challenging due to their biological complexity. To address this issue, we investigated the collective dynamics of metallodielectric Janus particles driven by an alternating current (AC) electric field. The propulsion speed and direction of these synthetic swimmers can be finely tuned by adjusting the magnitude and frequency of the applied electric field [1,2]. In this study, we explored the frequency-dependent collective behavior of Janus particles in moderately dense suspensions under AC electric fields ranging from 1 kHz to 100 kHz. At lower frequencies, the particles formed dynamic, transient clusters, consistent with previous reports [3]. By systematically varying the particle diameter and the thickness of the chromium coating, we modulated the particles' self-propulsion characteristics. Furthermore, we investigated binary mixtures of Janus particles with differing motilities to study collective phenomena in dynamically heterogeneous systems. [1] S. Gangwal, O J. Cayre, MZ. Bazant and OD. Velev, Phys. Rev. Lett. 100, 058302 (2008). [2] J. Yan, et al., Nat. Mater. 15, 1095-1099 (2016). [3] I. Buttinoni, et al., Phy. Rev. Lett. 110, 238301 (2013).

Colors in organisms can be produced either chemically by pigments or physically by the constructive interference of light scattered by biophotonic nanostructures and sometimes as a combination of both. Fade-proof, saturated structural colors that have evolved over millions of years of selective optimization are an ideal source to look for natural solutions to our current technological challenges in optics, and sensing. However, given that the underlying nanostructures are overwhelmingly diverse in form and function, their characterization has suffered for over a century. I have pioneered the use of synchrotron Small Angle X-ray Scattering (SAXS) as a high throughput technique to structurally and optically characterize integumentary photonic nanostructures from hundreds of species in a comparative fashion. This led to the discovery of the first single gyroid crystals in biology within the iridescent green wing scales of certain butterflies whose self-assembly beautifully pre-empts our current engineering approaches and more recently, within the feathers of some leafbirds. The latter is the first directly phase-separated single gyroid known to science and at the hard to achieve visible optical length scales. I will broadly summarize our current state of knowledge about the functional morphology of organismal structural colors in birds, butterflies and beetles, with a focus on what role(s) gel transitions play in the assembly of these complex biological nanostructures and conclude with some biomimetic case studies on replicating the vibrant colors in nature using biopolymeric wastes for a circular economy.

All around us, we see individuals moving in groups, a phenomenon known as collective behavior. Living and traveling in groups poses many benefits to group members. One such benefit is that knowledge and tasks can be distributed amongst constituents. Thus, only a few individuals have pertinent information for performing any given task and must lead the rest of the group in this task. Traveling in groups, however, can also pose challenges, particularly in the face of obstacles and confinements. We introduce a minimal model for collective behavior in which individuals interact via aligning and non-reciprocal, cohesive torques [1]. These torques represent the competing tendencies of individuals to coalesce and to move in the same direction. By changing the strength and range of these torque interactions, we uncover six states which we distinguish via their static and dynamic properties: a disperse state, a multiple worm state, a line state, a persistent worm state, a rotary worm state, and an aster state. Using the emergent persistent worm state from this model, we then investigate the ability of designated leaders to guide a group towards a moving target. Leaders are randomly chosen group members who chemotactically sense and turn towards the moving target. To investigate the robustness of the group’s chasing ability in different scenarios, we assign several different target dynamics and speeds. Finally, we investigate the ability of the persistent worm to navigate different confining geometries. [1] Shea, J. and Stark, H. Emergent collective behavior of cohesive, aligning particles. Eur. Phys. J. E 48, 22 (2025).

Biological systems achieve precise control over motion by dynamically regulating cytoskeletal networks, where motor proteins drive directed transport and coordinate large-scale organization. However, replicating this level of spatial and temporal coordination in vitro remains a challenge. In vitro reconstituted active matter systems composed of cytoskeletal components, such as microtubules and motor proteins, have successfully generated internally driven chaotic flows. Yet, unlike their cellular counterparts, these systems typically lack regulatory mechanisms that enable adaptive organization. Here, we present a novel strategy that leverages in vitro motor protein synthesis to dynamically control microtubule-based active matter, enabling self-regulation and spatial organization. By integrating synthesis-driven modulation, we establish a self-adaptive framework that transitions from a passive to an active state via a bending instability, where local active stress overcomes elastic turbulence. This tunable control over emergent behaviors brings in vitro active matter closer to the spatiotemporal precision observed in living systems.

Active matter systems consist of energy-consuming units that generate work, leading to self-driven motion and collective behavior. In active solids, these units are embedded in elastic matrices, where feedback between internal stresses and matrix deformation can result in dynamic phenomena such as spontaneous oscillations. In this project, we explore a novel computing platform by coupling active colloidal particles with DNA-based molecular computing networks. The active particles generate localized forces, while the DNA network provides programmable information processing. By integrating these two systems, we aim to develop dynamic, responsive materials with computing capabilities. This approach opens new directions for smart material design and unconventional computing at the interface of active matter and molecular logic.

Growth drives cellular dynamics in dense aggregates, including bacterial colonies, developing tissues, and tumors. However, its effects on other relevant activities have not received sufficient attention. Here, we investigate the underlying physical principles emerging from the interplay of unconstrained growth, steric repulsion, and motility in a minimal agent-based model of exponentially growing, three-dimensional spheroids. Our results reveal a motility-induced mixing transition: Despite cell-scale diffusion, cell lineages remain confined to their local environment until a certain motility threshold is reached, after which the system transitions to tangential superdiffusivity and global cell mixing, with a diverging timescale near the transition, reminiscent of glassy dynamics. Using a phenomenological model, we identify two effects governing this transition: Steric interactions that suppress active motion below a threshold, and the expanding nature of the system, which inhibits complete mixing. The results provide a baseline for identifying additional biological mechanisms in experiments and could be relevant for competition and heterogeneous tumor evolution.

Biological materials operate far from equilibrium, continuously converting chemical energy—such as from ATP—into mechanical motion. These systems also possess complex fluid properties, often exhibiting long-lived spatiotemporal correlations, including features reminiscent of glassy behavior. In this study, we present a hydrodynamic framework that integrates material memory into the description of chemically driven active fluids. Using a fundamental relation between correlation and response, we derive the constitutive relations governing their behavior.

While searching for resources, living organisms modulate their motility by alternating between movement and pauses in response to local sensory cues. When optimal conditions can be characterized by only a few physical variables—such as light intensity in phototactic micro-organisms—low-dimensional thresholding may serve as an effective strategy. In contexts involving higher-dimensional sensory inputs, however, some variables exhibit trade-offs, necessitating adaptive, higher-order information integration. Human behavior in social gathering spaces serves as a clear example of this, with multidimensional social–physical variables governing motion. Investigating how humans explore such multidimensional social spaces presents a compelling challenge for active‑matter physics; extending motility analyses to cognitively complex organisms can offer direct comparisons with other active‑matter systems and provide broader insights into universal behaviors. In this study, we analyze visitor trajectories within an approximately 200 × 300 m exhibition hall at Tokyo Big Sight, one of Japan’s largest convention venues. Visitors move freely between booths—sometimes proceeding directly to planned destinations, other times moving around to discover new information—resulting in complex spatiotemporal migration patterns that are challenging to reproduce in simulation. Using a dataset of thousands of trajectory coordinates, we characterize the statistical properties of human motion in open exhibition spaces as an active‑matter system, providing insights into the underlying dynamics. These insights further have practical implications for ensuring visitor safety and comfort.

Non-reciprocal interactions, which effectively violate Newton’s third law, have recently attracted attention in the fields of active matter and non-equilibrium physics. We investigate the spatiotemporal pattern formation described by the one-dimensional non-reciprocal Swift-Hohenberg (NRSH) model, focusing on the bifurcation structure related to non-equilibrium phase transitions driven by non-reciprocity. Based on numerical time simulations and spatiotemporal Fourier spectra, we identify and quantify five characteristic spatiotemporal patterns: a trivial disordered phase, a stationary aligned phase, a standing wave swap phase, a modulated traveling chiral-swap phase, and a traveling wave chiral phase, and construct corresponding phase diagrams. Further, we derive a reduced low-dimensional dynamical system that facilitates a deeper analysis by focusing on the dominant spatial Fourier modes. The bifurcation analysis of this reduced system reveals the mechanisms of the observed phase transitions. We demonstrate that a Turing, a wave, and a pitchfork bifurcation, respectively, describe the transition from the disordered phase to the aligned phase, from the aligned to the chiral phase, and from the aligned to the chiral phase. These theoretically obtained bifurcation loci agree well with the numerically obtained phase boundaries. Our findings highlight that the coexistence of reciprocal and non-reciprocal interactions gives rise to a rich bifurcation structure, including dynamical phases with amplitude oscillations, such as the swap and chiral-swap phases. The existence of a degenerate point where all phase boundaries converge suggests a connection to higher-codimension bifurcations, such as the Bogdanov-Takens bifurcation with O(2) symmetry, sometimes referred to as a “critical exceptional point.” The resulting global bifurcation structure provides a more profound insight into the universality of pattern formation in non-reciprocal systems.

While active matter and biological systems are intrinsically nonequilibrium and fluctuating, the existence of topologically protected transport phenomena has been theoretically proposed using the methodology inspired by wavenumber topology in solid-state physics. Recently, edge flow, i.e., robust unidirectional flow along the system boundary, predicted by the bulk-boundary correspondence, was experimentally realized in systems composed of active particles with self-spinning or chiral motion. However, to design topological phenomena in active matter systems, it is desired to establish methods for controlling the topological phenomena without altering the properties of active particles. To this end, here we aim to realize topological phenomena in a dense bacterial suspension, by using microfabricated geometrical structures with nontrivial wavenumber topology. The microfabricated structures consist of circle-shaped wells connected by channels with an asymmetric, ratchet-like shape which induce unidirectional flow therein. In the case of asymmetric kagome networks, we find edge localization by measuring the fluorescent intensity of dyed bacteria, which results from the characteristic rectified collective flow of bacteria driven by the asymmetric channels. We investigate how the bacterial flow may generate edge localization by combining the experimentally obtained velocity field and simulated particle transport. We also discuss the essential properties of geometrical and lattice design for realizing topological phenomena in bacterial collective motion by tuning the geometry of the microfabricated devices. We expect our experimental results may pave the way toward establishing a control and design principle of topological transport phenomena in such active matter systems.

Directed motion up a concentration gradient is crucial for the survival and maintenance of numerous biological systems, such as sperms moving towards an egg during fertilization or transport cargo along microtubules by kinesin motors. These systems are characterised by the presence of chirality, manifested as a rotational torque as in the case of sperms, or the presence of active myosin motors in specific locations as in the case of microtubules. In both cases, the respective characteristic properties play a vital role in facilitating directed motion. In this study, we first examine the simplest case of a chiral active particle connected to a passive particle in a spatially varying activity field. We demonstrate that this minimal setup can exhibit rich emergent tactic behaviors, with the chiral torque serving as the tuning parameter. Notably, when the chiral torque is sufficiently large, even a small passive particle enables the system to display the desired accumulation behavior. Our results further show that in the dilute limit, this desired accumulation behavior persists despite the presence of excluded volume effects. Additionally, interconnected chiral active particles exhibit emergent chemotaxis beyond a critical chain length, with trimers and longer chains exhibiting strong accumulation at sufficiently high chiral torques. As a second part of this study, we study Rouse chains where the constituent monomers could be active or passive Brownian particles, in a spatially varying activity field. We focus on how the arrangement of active units within the polymer affects its steady-state and dynamic behavior and how they can be optimized to achieve high accumulation or rapid motility. This study provides valuable insights into the design principles of hybrid bio-molecular devices of the future.

The cell cortex undergoes both viscous and elastic deformations in response to internal and external stresses. The internal active stresses arise from the actomyosin meshwork within the cortex and drive cellular flows and morphogenesis during development. To shed light on the role of mechanics in these processes, we start from first principles at microscopic scales to systematically construct a continuum mechanical model of the cell cortex (known as the active fluid surface). We then develop a unified numerical framework based on Boundary Element Methods to simulate the full nonlinear dynamics of this actively deforming surface. Our results demonstrate that a chemo-hydrodynamic instability resulting from the interplay between active stress and surface deformation is sufficient to explain some of the self-organized dynamics such as cell locomotion and division.

Chiral active matter, which breaks both parity symmetry and detailed balance, is widespread in living systems. These systems display rich non-equilibrium phenomena such as odd-response-induced phase separation, directed edge currents, and chiral oscillatory dynamics. To investigate chiral active matter within a minimal yet fundamental framework, we first introduce a lattice gas model. Our results show that at low temperatures, the system undergoes coarsening into condensates with characteristic chiral structures that differ significantly from those of the classical Ising model. In the steady state, these condensates form faceted, crystal-like shapes. Their interfaces exhibit persistent edge currents and form characteristic angles with respect to the lattice axes. To generalize our findings, we further develop a continuum approach by adding an active edge current term to active model B. This extension captures the essential features of chirality in phase separation and highlights the crucial role of edge currents in shaping interfacial dynamics and symmetry-breaking patterns in chiral active systems.