Session A30: Microscale Flows: Locomotion

Inertial three-sphere swimmer

The Najafi-Golestanian microswimmer (Najafi and Golestanian, Phys. Rev. E, 69,

062901, 2004), which consists of three spheres linked by rigid rods, represents a simple,

elegant way for self-propulsion at low Reynolds numbers. In this work, we use numerical

simulations based on the immersed boundary method to go beyond the low-Reynolds-

number regime and examine the impact of fluid inertia on the propulsion characteristics

of the swimmer. Our results show that the inertial effect modifies not only the speed but

also the direction of propulsion depending on the different parameters of the system. The

findings may inform the design of artificial swimmers that operate at small but finite Reynolds numbers.   

Geometrical effect on self-phoresis

Within a unified formulation, we discuss the effect of geometry, distribution of surface flux, and phoretic mobility on the motion of microswimmer. Appropriate scaling of the speed with the case of a spherical particle allows a dimensionless measure of the geometrical performance of a microswimmer. For bipartite designs, we study the cases of source-sink and source-inert with piecewise uniform flux over complementary surface regions for a set of deformed spheres.    

Reinforcement learning of a multi-link swimmer

The use of machine learning techniques in the development of microscopic swimmers has drawn considerable attention in recent years. In particular, reinforcement learning has been shown useful in enabling a swimmer to learn effective propulsion strategies through its interactions with the surroundings. In this talk, we will report results on integrating reinforcement learning into the design of a multi-link swimmer. With minimal degrees of freedom, the learning algorithm identifies the locomotory gaits of the classical Purcell's swimmer. We will discuss other effective strategies identified by reinforcement learning with increased degrees of freedom.   

Swimming Kinematics of Achiral Microswimmers in Viscous Media

As opposed to more common flexible and chiral structures which can swim in bulk fluid, geometrically simpler achiral structures have often relied on nearby solid boundaries to break the symmetry of cyclic swimming strokes. However, achiral microswimmers with at least two planes of geometric symmetry have been found capable of propulsion in the absence of confining walls. Here, microswimmers consisting of three and four concatenated magnetic microparticles, forming arc structures with two planes of symmetry, are fabricated through self-assembly. As achiral microswimmers are envisioned for biological applications where the microenvironment is made up of mostly non-Newtonian fluids, using a uniform rotational magnetic field, we investigated their swimming kinematics, specifically velocity, precession angle, and their ability to change direction in a series of dilute methylcellulose solutions which mimic biofluids. Non-linear relationships are observed between methylcellulose concentration and propulsion characteristics. The observed swimming behaviors may enable the development of future achiral microswimmer designs and control strategies for propulsion in complex media.   

Not Participating

There is a growing interest in developing artificial microswimmers that can self-propel like swimming microorganisms for potential biomedical applications. A fundamental challenge is the design of effective locomotory gaits that can overcome the constraints due to the dominance of viscous forces. In addition, the swimmer needs to adapt its gaits in order to re-orient and reach the target locations. In this talk, we report our progress in integrating machine learning techniques in the design of artificial microswimmers. We will discuss how reinforcement learning can be leveraged to enable complex maneuvers of the swimmer. The results demonstrate the vast potential of this new approach in designing smart microswimmers that can perform sophisticated tasks.   

Magnetic Navigation of Artificial Bacteria Flagella in Blood and Water

 Artificial bacteria flagella (ABFs) are magnetic helical micro-robots that can be remotely controlled via a uniform, rotating magnetic field. While the control of a single swimmer with the uniform magnetic field is straightforward, the independent control of multiple ABFs is an unsolved problem. We demonstrate such independent control by exploiting the distinct geometries of the ABFs through an analytical solution and a reinforcement learning algorithm. We compare the two algorithms and demonstrate the superiority of  reinforcement learning in achieving multiple objectives. The results  demonstrate, effective independent navigation of  realistic micro-swimmers in a viscous flow field. Moreover we demonstrate the navigation of ABFs in microscale simulations of blood flows.   

Mathematical Modeling of Reactive Swimming Droplets

A simple two-variable model for self propulsion of reactive swimming droplets is developed. The model is capable of predicting experimentally observed self propulsion for systems exhibiting a decrease in surface tension with reaction as well. A linear stabilityanalysis is carried out to determine stable static and unstable self-propelling regimes. It is shown that the instability can lead to both monotonic as well as oscillatory propulsion. The self-propelled motion of reactive droplets is a consequence of Marangoni flow driven by gradients in interfacial tension. While the interfacial convective transport of adsorbed surfactants stabilizes the droplet, the advective influx of free surfactants from the ambient bulk toward the interface is the key destabilizing effect. With the help of stability analysis, the role of several parameters that affect the propulsion dynamics, such as droplet size, the reaction rate, and relative activity of reactant and product surfactants, is investigated.   

Inertialess jet propulsion of hydrogels

Small devices designed for biomimetic locomotion need to exploit flows that are not symmetric in time (non-reciprocal) to escape the constraints of the scallop theorem and undergo net motion. In this work, we consider the dynamics of asymmetrically-coated thermoresponsive hydrogel ribbons under periodic heating and cooling in the confined space between two planar surfaces. As the result of the temperature changes, the volume and thus the shape of the slender hydrogel change, which lead to repeated cycles of bending and elastic relaxation, and to net locomotion. Unlike biological slender swimmers, the non-reciprocal bending of the gel centreline is not sufficient to explain for the overall swimming motion. We show instead that the swimming of the gel results from the flux of water periodically emanating from (or entering) the gel itself due to its shrinking (or swelling). The associated flows induce viscous stresses that lead to a net propulsive force on the gel. We derive a theoretical model for this hypothesis of jet-driven propulsion, which leads to excellent agreement with our experiments.