Smart active particles learn and transcend bacterial foraging strategies.

Throughout evolution, bacteria and other microorganisms have learned efficient foraging strategies that exploit characteristic properties of their unknown environment. While much research has been devoted to the exploration of statistical models describing the dynamics of foraging bacteria and other (micro-) organisms, little is known, regarding the question of how good the learned strategies actually are. This knowledge gap is largely caused by the absence of methods allowing to systematically develop alternative foraging strategies to compare with. In the present work, we use deep reinforcement learning to show that a smart run-and-tumble agent, which strives to find nutrients for its survival, learns motion patterns that are remarkably similar to the trajectories of chemotactic bacteria. Strikingly, despite this similarity, we also find interesting differences between the learned tumble rate distribution and the one that is commonly assumed for the run and tumble model. We find that these differences equip the agent with significant advantages regarding its foraging and survival capabilities. Our results uncover a generic route to use deep reinforcement learning for discovering search and collection strategies that exploit characteristic but initially unknown features of the environment. These results can be used, e.g., to program future microswimmers, nanorobots, and smart active particles for tasks like searching for cancer cells, micro-waste collection, or environmental remediation.

Collective self-optimization of communicating active particles.

The quest for how to collectively self-organize in order to maximize the survival chances of the members of a social group requires finding an optimal compromise between maximizing the well-being of an individual and that of the group. Here we develop a minimal model describing active individuals which consume or produce, and respond to a shared resource-such as the oxygen concentration for aerotactic bacteria or the temperature field for penguins-while urging for an optimal resource value. Notably, this model can be approximated by an attraction-repulsion model, but, in general, it features many-body interactions. While the former prevents some individuals from closely approaching the optimal value of the shared "resource field," the collective many-body interactions induce aperiodic patterns, allowing the group to collectively self-optimize. Arguably, the proposed optimal field-based collective interactions represent a generic concept at the interface of active matter physics, collective behavior, and microbiological chemotaxis. This concept might serve as a useful ingredient to optimize ensembles of synthetic active agents or to help unveil aspects of the communication rules which certain social groups use to maximize their survival chances.

Detecting Isotachophoresis Zones Hidden in Noise Using Signal Processing.

Lowering the limit of detection in chemical or biochemical analysis is key to extending the application scope of sensing schemes. Usually, this is related to an increased instrumentation effort, which in turn precludes many commercial applications. We demonstrate that the signal-to-noise ratio of isotachophoresis-based microfluidic sensing schemes can be substantially increased merely by postprocessing of recorded signals. This becomes possible by exploiting knowledge about the physics of the underlying measurement process. The implementation of our method is based on microfluidic isotachophoresis and fluorescence detection, for which we take advantage of the physics of electrophoretic sample transport and the structure of noise in the imaging process. We demonstrate that by processing only 200 images, the detectable concentration, compared to the detection from a single image, is already lowered by 2 orders of magnitude without any additional instrumentation effort. Furthermore, we show that the signal-to-noise ratio is proportional to the square root of the number of fluorescence images, which leaves room for further lowering of the detection limit. In the future, our results could be relevant for various applications where the detection of minute sample amounts plays a role.

Writing Into Water.

Writing is an ancient communication technique dating back at least 30 000 years. While even sophisticated contemporary writing techniques hinge on solid surfaces for engraving or the deposition of ink, writing within a liquid medium requires a fundamentally different approach. The study here demonstrates the writing of lines, letters, and complex patterns in water by assembling lines of colloidal particles. Unlike established techniques for underwater writing on solid substrates, these lines are fully reconfigurable and do not require any fixation onto the substrate. Exploiting gravity, an ion-exchange bead (pen) is rolled across a layer of sedimented colloidal particles (ink). The pen evokes a hydrodynamic flow collecting ink-particles into a durable, high-contrast line along its trajectory. Deliberate substrate-tilting sequences facilitate pen-steering and thus drawing and writing. The experiments are complemented with a minimal model that quantitatively predicts the observed parameter dependence for writing in fluids and highlights the generic character of writing by line-assembly. Overall, the approach opens a versatile route for writing, drawing, and patterning fluids-even at the micro-scale.

Inverted Sedimentation of Active Particles in Unbiased ac Fields.

Gaining control over the motion of active particles is crucial for applications ranging from targeted cargo delivery to nanomedicine. While much progress has been made recently to control active motion based on external forces, flows, or gradients in concentration or light intensity, which all have a well-defined direction or bias, little is known about how to steer active particles in situations where no permanent bias can be realized. Here, we show that ac fields with a vanishing time average provide an alternative route to steering active particles. We exemplify this route for inertial active particles in a gravitational field, observing that a substantial fraction of them persistently travels in the upward direction upon switching on the ac field, resulting in an inverted sedimentation profile at the top wall of a confining container. Our results offer a generic control principle that could be used in the future to steer active motion, direct collective behaviors, and purify mixtures.

Charging of Dielectric Surfaces in Contact with Aqueous Electrolytes─the Influence of CO2.

The charge state of dielectric surfaces in aqueous environments is of fundamental and technological importance. Here, we study the influence of dissolved molecular CO2 on the charging of three chemically different surfaces (SiO2, Polystyrene, Perfluorooctadecyltrichlorosilane). We determine their charge state from electrokinetic experiments. We compare an ideal, CO2-free reference system to a system equilibrated against ambient CO2 conditions. In the reference system, the salt-dependent decrease of the magnitudes of ζ-potentials follows the expectations for a constant charge scenario. In the presence of CO2, the starting potential is lower by some 50%. The following salt-dependent decrease is weakened for SiO2 and inverted for the organic surfaces. We show that screening and pH-driven charge regulation alone cannot explain the observed effects. As an additional cause, we tentatively suggest dielectric regulation of surface charges due to a diffusively adsorbed thin layer of molecular CO2. The formation of such a dynamic layer, even at the hydrophilic and partially ionized silica surfaces, is supported by a minimal theoretical model and results from molecular simulations.

Active Refrigerators Powered by Inertia.

We present the operational principle for a refrigerator that uses inertial effects in active Brownian particles to locally reduce their (kinetic) temperature by 2 orders of magnitude below the environmental temperature. This principle exploits the peculiar but so-far unknown shape of the phase diagram of inertial active Brownian particles to initiate motility-induced phase separation in the targeted cooling regime only. Remarkably, active refrigerators operate without requiring isolating walls opening the route toward using them to systematically absorb and trap, e.g., toxic substances from the environment.

Resonant Nanopumps: ac Gate Voltages in Conical Nanopores Induce Directed Electrolyte Flow.

Inducing transport in electrolyte-filled nanopores with dc fields has led to influential applications ranging from nanosensors to DNA sequencing. Here we use the Poisson-Nernst-Planck and Navier-Stokes equations to show that unbiased ac fields can induce comparable directional flows in gated conical nanopores. This flow exclusively occurs at intermediate driving frequencies and hinges on the resonance of two competing timescales, representing space charge development at the ends and in the interior of the pore. We summarize the physics of resonant nanopumping in an analytical model that reproduces the results of numerical simulations. Our findings provide a generic route toward real-time controllable flow patterns, which might find applications in controlling the translocation of small molecules or nanocolloids.

Non-monotonic speed-dependence of microswimmers on wall distance.

While substrates naturally occur in most microswimmer experiments, their impact on the swimming performance is not well understood. In the present study, we functionalize substrates with polymer brushes of varying swelling properties, grafting densities and brush lengths to systematically modify and explore the substrate-swimmer interactions. Notably, the swimming speed does not monotonically change with brush thickness, but shows a distinct maximum at a certain intermediate thickness, which results from two counteracting factors: surface charge and surface roughness. The results show that the speed of thermophoretic microswimmers does not only depend on the particle properties but is also strongly influenced by the properties of the underlying substrate. This provides a route to control the speed of microswimmers via the underlying substrate, which could be applied in the future e.g. to design complex motility landscapes by patterning substrates with polymer brushes. It is expected that similar effects would occur for diffusio- and electrophoretic particles.

Shaping the gradients driving phoretic micro-swimmers: influence of swimming speed, budget of carbonic acid and environment.

pH gradient-driven modular micro-swimmers are investigated as a model for a large variety of quasi-two-dimensional chemi-phoretic self-propelled entities. Using three-channel micro-photometry, we obtain a precise large field mapping of pH at a spatial resolution of a few microns and a pH resolution of [Formula: see text] units for swimmers of different velocities propelling on two differently charged substrates. We model our results in terms of solutions of the three-dimensional advection-diffusion equation for a 1:1 electrolyte, i.e. carbonic acid, which is produced by ion exchange and consumed by equilibration with dissolved [Formula: see text]. We demonstrate the dependence of gradient shape and steepness on swimmer speed, diffusivity of chemicals, as well as the fuel budget. Moreover, we experimentally observe a subtle, but significant feedback of the swimmer's immediate environment in terms of a substrate charge-mediated solvent convection. We discuss our findings in view of different recent results from other micro-fluidic or active matter investigations. We anticipate that they are relevant for quantitative modelling and targeted applications of diffusio-phoretic flows in general and artificial micro-swimmers in particular.

Actomyosin Contraction Induces In-Bulk Motility of Cells and Droplets.

Cell crawling on two-dimensional surfaces is a relatively well-understood phenomenon that is based on actin polymerization at a cell's front edge and anchoring on a substrate, allowing the cell to pull itself forward. However, some cells, such as cancer cells invading a three-dimensional matrigel, can also swim in the bulk, where surface adhesion is impossible. Although there is strong evidence that the self-organized engine that drives cells forward in the bulk involves myosin, the specific propulsion mechanism remains largely unclear. Here, we propose a minimal model for in-bulk self-motility of a droplet containing an isotropic and compressible contractile gel, representing a cell extract containing a disordered actomyosin network. In our model, contraction mediates a feedback loop between myosin-induced flow and advection-induced myosin accumulation, which leads to clustering and locally enhanced flow. The symmetry of such flow is then spontaneously broken through actomyosin-membrane interactions, leading to self-organized droplet motility relative to the underlying solvent. Depending on the balance between contraction, diffusion, detachment rate of myosin, and effective surface tension, this motion can be either straight or circular. Our simulations and analytical results shed new light on in-bulk myosin-driven cell motility in living cells and provide a framework to design a novel type of synthetic active matter droplet potentially resembling the motility mechanism of biological cells.

Active Assembly of Spheroidal Photocatalytic BiVO4 Microswimmers.

We create single-component photocatalytic bismuth vanadate (BiVO4) microswimmers with a spheroidal shape that move individually upon irradiation without any asymmetrization step. These particles form active assemblies which we investigate combining an experimental approach with numerical simulations and analytical calculations. We systematically explore the speed and assembly of the swimmers into clusters of up to four particles and find excellent agreement between experiment and theory, which helps us to understand motion patterns and speed trends. Moreover, different batches of particles can be functionalized separately, making them ideal candidates to fulfill a multitude of tasks, such as sensing or environmental remediation. To exemplify this, we coat our swimmers with silica (SiO2) and selectively couple some of their modules to fluorophores in a way which does not inhibit self-propulsion. The present work establishes spheroidal BiVO4 microswimmers as a versatile platform to design multifunctional microswimmers.

Clustering-induced velocity-reversals of active colloids mixed with passive particles.

Recent experiments have shown that colloidal suspensions can spontaneously self-assemble into dense clusters of various internal structures, sizes, and dynamical properties when doped with active Janus particles. Characteristically, these clusters move ballistically during their formation but dynamically revert their velocity and temporarily move opposite to the self-propulsion direction of the Janus particles they contain. Here, we explore a simple effective model of colloidal mixtures that allows reproducing most aspects seen in experiments, including the morphology and the velocity-reversal of the clusters. We attribute the latter to the nonreciprocal phoretic attractions of the passive particles to the active colloids' caps, taking place even at close contact and pushing the active particles backwards. When the phoretic interactions are repulsive, in turn, they cause dynamical aggregation of passive colloids in the chemical density minima produced by the active particles, as recently seen in experiments; in other parameter regimes, they induce traveling fronts of active particles pursued by passive ones coexisting with an active gas.

Synthetic Chemotaxis and Collective Behavior in Active Matter.

The ability to navigate in chemical gradients, called chemotaxis, is crucial for the survival of microorganisms. It allows them to find food and to escape from toxins. Many microorganisms can produce the chemicals to which they respond themselves and use chemotaxis for signaling, which can be seen as a basic form of communication, allowing ensembles of microorganisms to coordinate their behavior, for example, during embryogenesis, biofilm formation, or cellular aggregation. For example, Dictyostelium cells use signaling as a survival strategy: when starving, they produce certain chemicals toward which other cells show taxis. This leads to aggregation of the cells resulting in a multicellular aggregate that can sustain long starvation periods. Remarkably, the past decade has led to the development of synthetic microswimmers, which can self-propel through a solvent, analogously to bacteria and other microorganisms. The mechanism underlying the self-propulsion of synthetic microswimmers like camphor boats, droplet swimmers, and in particular autophoretic Janus colloids involves the production of certain chemicals. As we will discuss in this Account, the same chemicals (phoretic fields) involved in the self-propulsion of a (Janus) microswimmer also act on other ones and bias their swimming direction toward (or away from) the producing microswimmer. Synthetic microswimmers therefore provide a synthetic analogue to motile microorganisms interacting by taxis toward (or away from) self-produced chemical fields. In this Account, we review recent progress in the theoretical description of synthetic chemotaxis mainly based on simulations and field theoretical descriptions. We will begin with single motile particles leaving chemical trails behind with which they interact themselves, leading to effects like self-trapping or self-avoidance. Besides these self-interactions, in ensembles of synthetic motile particles each particle also responds to the chemicals produced by other particles, inducing chemical (or phoretic) cross-interactions. When these interactions are attractive, they commonly lead to clusters, even at low particle density. These clusters may either proceed toward macrophase separation, resembling Dictyostelium aggregation, or, as shown very recently, lead to dynamic clusters of self-limited size (dynamic clustering) as seen in experiments in autophoretic Janus colloids. Besides the classical case where chemical interactions are attractive, this Account discusses, as its main focus, repulsive chemical interactions, which can create a new and less known avenue to pattern formation in active systems leading to a variety of pattern, including clusters which are surrounded by shells of chemicals, traveling waves and more complex continuously reshaping patterns. In all these cases "synthetic signalling" can crucially determine the collective behavior of synthetic microswimmer ensembles and can be used as a design principle to create patterns in motile active particles.

Motility-Induced Temperature Difference in Coexisting Phases.

Unlike in thermodynamic equilibrium where coexisting phases always have the same temperature, here we show that systems comprising "active" self-propelled particles can self-organize into two coexisting phases at different kinetic temperatures, which are separated from each other by a sharp and persistent temperature gradient. Contrasting previous studies that have focused on overdamped descriptions of active particles, we show that a "hot-cold coexistence" occurs if and only if accounting for inertia, which is significant, e.g., in activated dusty plasmas, microflyers, whirling fruits, or beetles at interfaces. Our results exemplify a route to use active particles to create a self-sustained temperature gradient across coexisting phases. This phenomenon is fundamentally beyond equilibrium physics and is accompanied by a slow coarsening law with an exponent significantly smaller than the universal 1/3 exponent seen in both equilibrium systems and overdamped active Brownian particles.

Propagating density spikes in light-powered motility-ratchets.

Combining experiments and computer simulations, we use a spatially periodic and flashing light-field to direct the motion of phototactic active colloids. Here, the colloids self-organize into a density spike pattern, which resembles a shock wave and propagates over long distances, almost without dispersing. The underlying mechanism involves a synchronization of the colloids with the light-field, so that particles see the same intensity gradient each time the light-pattern is switched on, but no gradient in between (for example). This creates pulsating transport whose strength and direction can be controlled via the flashing protocol and the self-propulsion speed of the colloids. Our results might be useful for drug delivery applications and can be used to segregate active colloids by their speed.

Which interactions dominate in active colloids?

Despite mounting evidence that the same gradients, which active colloids use for swimming, induce important cross-interactions (phoretic interactions), they are still ignored in most many-body descriptions, perhaps to avoid complexity and a zoo of unknown parameters. Here we derive a simple model, which reduces phoretic far-field interactions to a pair-interaction whose strength is mainly controlled by one genuine parameter (swimming speed). The model suggests that phoretic interactions are generically important for autophoretic colloids (unless effective screening of the phoretic fields is strong) and should dominate over hydrodynamic interactions for the typical case of half-coating and moderately nonuniform surface mobilities. Unlike standard minimal models, but in accordance with canonical experiments, our model generically predicts dynamic clustering in active colloids at a low density. This suggests that dynamic clustering can emerge from the interplay of screened phoretic attractions and active diffusion.

Light-controlled assembly of active colloidal molecules.

Thanks to a constant energy input, active matter can self-assemble into phases with complex architectures and functionalities such as living clusters that dynamically form, reshape, and break-up, which are forbidden in equilibrium materials by the entropy maximization (or free energy minimization) principle. The challenge to control this active self-assembly has evoked widespread efforts typically hinging on engineering of the properties of individual motile constituents. Here, we provide a different route, where activity occurs as an emergent phenomenon only when individual building blocks bind together in a way that we control by laser light. Using experiments and simulations of two species of immotile microspheres, we exemplify this route by creating active molecules featuring a complex array of behaviors, becoming migrators, spinners, and rotators. The possibility to control the dynamics of active self-assembly via light-controllable nonreciprocal interactions will inspire new approaches to understand living matter and to design active materials.

Membrane penetration and trapping of an active particle.

The interaction between nano- or micro-sized particles and cell membranes is of crucial importance in many biological and biomedical applications such as drug and gene delivery to cells and tissues. During their cellular uptake, the particles can pass through cell membranes via passive endocytosis or by active penetration to reach a target cellular compartment or organelle. In this manuscript, we develop a simple model to describe the interaction of a self-driven spherical particle (moving through an effective constant active force) with a minimal membrane system, allowing for both penetration and trapping. We numerically calculate the state diagram of this system, the membrane shape, and its dynamics. In this context, we show that the active particle may either get trapped near the membrane or penetrate through it, where the membrane can either be permanently destroyed or recover its initial shape by self-healing. Additionally, we systematically derive a continuum description allowing us to accurately predict most of our results analytically. This analytical theory helps in identifying the generic aspects of our model, suggesting that most of its ingredients should apply to a broad range of membranes, from simple model systems composed of magnetic microparticles to lipid bilayers. Our results might be useful to predict the mechanical properties of synthetic minimal membranes.

Simultaneous Control of Multispecies Particle Transport and Segregation in Driven Lattices.

We provide a generic scheme to separate the particles of a mixture by their physical properties like mass, friction, or size. The scheme employs a periodically shaken two-dimensional dissipative lattice and hinges on a simultaneous transport of particles in species-specific directions. This selective transport is achieved by controlling the late-time nonlinear particle dynamics, via the attractors embedded in the phase space and their bifurcations. To illustrate the spectrum of possible applications of the scheme, we exemplarily demonstrate the separation of polydisperse colloids and mixtures of cold thermal alkali atoms in optical lattices.