Search

This Supporting Information includes information regarding the magnetic field of the actuator magnet, MR-LF-S (which has the same geometry as MR-LF and a soft compartment), and a table comparing MR-LF to other small-scale, flexible magnetic crawler robots. Corresponding author email: yong.kong@utah.edu

Medical micro/nanorobots have received tremendous attention over the past decades owing to their potential to be navigated into hard-to-reach tissues for a number of biomedical applications ranging from targeted drug/gene delivery, bio-isolation, detoxification, to nanosurgery. Despite the great promise, the majority of the past demonstrations are primarily under benchtop or in vitro conditions. Many developed micro/nanoscale propulsion mechanisms are based on the assumption of a homogeneous, Newtonian environment, while realistic biological environments are substantially more complex. Moving toward practical medical use, the field of micro/nanorobotics must overcome several major challenges including propulsion through complex media (such as blood, mucus, and vitreous) as well as deep tissue imaging and control in vivo. In this review article, we summarize the recent research efforts on investigating how various complexities in biological environments impact the propulsion of micro/nanoswimmers. We also highlight the emerging technological approaches to enhance the locomotion of micro/nanorobots in complex environments. The recent demonstrations of in vivo imaging, control and therapeutic medical applications of such micro/nanorobots are introduced. We envision that continuing materials and technological innovations through interdisciplinary collaborative efforts can bring us steps closer to the fantasy of "swallowing a surgeon".

Biological and artificial microswimmers often encounter fluid media with non-Newtonian rheological properties. In particular, many biological fluids such as blood and mucus are shear-thinning. Recent studies have demonstrated how shear-thinning rheology can impact substantially the propulsion performance in different manners. In this work, we examine the effect of geometrical shape upon locomotion in a shear-thinning fluid using a prolate spheroidal squirmer model. We use a combination of asymptotic analysis and numerical simulations to quantify how particle geometry impacts the speed and the energetic cost of swimming. The results demonstrate the advantages of spheroidal over spherical swimmers in terms of both swimming speed and energetic efficiency when squirming through a shear-thinning fluid. More generally, the findings suggest the possibility of tuning the swimmer geometry to better exploit non-Newtonian rheological behaviours for more effective locomotion in complex fluids.

The effects of viscoelasticity have been shown to manifest themselves via symmetry breaking. In this investigation, we show a novel phenomenon that arises from this idea. We observe that when a dense sphere is rotated near a wall (the rotation being aligned with the wall-normal direction and gravity), it levitates to a fixed distance away from the wall. Since the shear is larger in the gap (between the sphere and the wall) than in the open side of the sphere, the shear-induced elastic stresses are thus asymmetric, resulting in a net elastic vertical force that balances the weight of the sphere. We conduct experiments, theoretical models and numerical simulations for rotating spheres of various sizes and densities in a Boger-type fluid. In the small-Deborah-number range, the results are collapsed into a universal trend by considering a dimensionless group of the ratio of elastic to gravitational forces.

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 swimmers to learn effective propulsion strategies through its interactions with the surroundings. In this work, we apply a reinforcement learning approach to identify swimming gaits of a multi-link model swimmer. The swimmer consists of multiple rigid links connected serially with hinges, which can rotate freely to change the relative angles between neighboring links. Purcell [“Life at low Reynolds number,” Am. J. Phys. 45, 3 (1977)] demonstrated how the particular case of a three-link swimmer (now known as Purcell's swimmer) can perform a prescribed sequence of hinge rotation to generate self-propulsion in the absence of inertia. Here, without relying on any prior knowledge of low-Reynolds-number locomotion, we first demonstrate the use of reinforcement learning in identifying the classical swimming gaits of Purcell's swimmer for case of three links. We next examine the new swimming gaits acquired by the learning process as the number of links increases. We also consider the scenarios when only a single hinge is allowed to rotate at a time and when simultaneous rotation of multiple hinges is allowed. We contrast the difference in the locomotory gaits learned by the swimmers in these scenarios and discuss their propulsion performance. Taken together, our results demonstrate how a simple reinforcement learning technique can be applied to identify both classical and new swimming gaits at low Reynolds numbers.

Particle–wall interactions have broad biological and technological applications. In particular, some artificial microswimmers capitalize on their translation–rotation coupling near a wall to generate directed propulsion. Emerging biomedical applications of these microswimmers in complex biological fluids prompt questions on the impact of non-Newtonian rheology on their propulsion. In this work, we report some intriguing effects of shear-thinning rheology, a ubiquitous non-Newtonian behaviour of biological fluids, on the translation–rotation coupling of a particle near a wall. One particularly interesting feature revealed here is that the wall-induced translation by rotation can occur in a direction opposite to what might be intuitively expected for an object rolling on a solid substrate. We elucidate the underlying physical mechanism and discuss its implications on the design of micromachines and bacterial motion near walls in complex fluids.

Many biological fluids display shear-thinning rheology, where the viscosity decreases with an increasing shear rate. To better understand how this non-Newtonian rheology affects the motion of biological and artificial micro-swimmers, recent efforts have begun to seek answers to fundamental questions about active bodies in shear-thinning fluids. Previous analyses based on a squirmer model have revealed non-trivial variations of propulsion characteristics in a shear-thinning fluid via the reciprocal theorem. However, the reciprocal theorem approach does not provide knowledge about the flow surrounding the squirmer. In this work, we fill in this missing information by calculating the non-Newtonian correction to the flow analytically in the asymptotic limit of small Carreau number. In particular, we investigate the local effect due to viscosity reduction and the non-local effect due to induced changes in the flow; we then quantify their relative importance to locomotion in a shear-thinning fluid. Our results demonstrate cases where the non-local effect can be more significant than the local effect. These findings suggest that caution should be exercised when developing physical intuition from the local viscosity distribution alone around a swimmer in a shear-thinning fluid.

Some micro-organisms and artificial micro-swimmers propel at low Reynolds numbers (Re) via the interaction of their flexible appendages with the surrounding fluid. While their locomotion has been extensively studied with a Newtonian fluid assumption, in realistic biological environments these micro-swimmers invariably encounter rheologically complex fluids. In particular, many biological fluids such as blood and different types of mucus have shear-thinning viscosities. The influence of this ubiquitous non-Newtonian rheology on the performance of flexible swimmers remains largely unknown. Here, we present a first study to examine how shear-thinning rheology alters the fluid-structure interaction and hence the propulsion performance of elastic swimmers at low Re. Via a simple elastic swimmer actuated magnetically, we demonstrate that shear-thinning rheology can either enhance or hinder elastohydrodynamic propulsion, depending on the intricate interplay between elastic and viscous forces as well as the magnetic actuation. We also use a reduced-order model to elucidate the mechanisms underlying the enhanced and hindered propulsion observed in different physical regimes. These results and improved understanding could guide the design of flexible micro-swimmers in non-Newtonian fluids.

Theoretical and computational analyses show that a shear-thinning viscosity alone can cause a substantial enhancement to the propulsion of helical microswimmers.

Microorganisms and artificial microswimmers often need to swim through environments that are more complex than purely viscous liquids in their natural habitats or operational environments, such as gel-like mucus, wet soil, and aquifers. The question of how the properties of these complex environments affect locomotion has attracted considerable recent attention. In this paper, we present a theoretical model to examine how the additional resistance due to the network of stationary obstacles in a porous medium affects helical locomotion. Here, we focus on helical locomotion for its ubiquity as a propulsion mechanism adopted by many swimming bacteria and artificial microswimmers. We show that the additional resistance can have qualitatively different effects on various scenarios of helical locomotion: (1) a helical propeller driven by an external torque, (2) a free swimming bacterium consisting of a helical flagellum and a head, and (3) a cargo-carrying helical propeller driven by an external torque. Our results elucidate the subtle and significant differences between torqued helical propulsion versus force-free and torque-free swimming in a porous medium. We also remark on the limitations as well as potential connections of our results with experimental measurements of bacterial swimming speeds in polymeric solutions.

Artificial microswimmers offer exciting opportunities for biomedical applications. The goal of these synthetics is to swim like natural micro‐organisms through biological environments and perform complex tasks such as drug delivery and microsurgery. Extensive efforts in the past several decades have focused on generating propulsion at the microscopic scale, which has engendered a variety of artificial microswimmers based on different physical and physicochemical mechanisms. Yet, these major advancements represent only the initial steps toward successful biomedical applications of microswimmers in realistic scenarios. A next step is to design “smart” microswimmers that can adapt their locomotion behaviors in response to environmental factors. Herein, recent progress in the development of microswimmers with intelligent behaviors is surveyed in three major areas: 1) adaptive locomotion across different media, 2) tactic behaviors in response to environment stimuli, and 3) multifunctional swimmers that can perform complex tasks. The emerging technologies and novel approaches used in developing these “smart” microswimmers, which enable them to display behaviors similar to biological cells, are discussed.

Cell motility plays important roles in a range of biological processes, such as reproduction and infections. Studies have hypothesized that the ulcer-causing bacterium Helicobacter pylori invades the gastric mucus layer lining the stomach by locally turning nearby gel into sol, thereby enhancing its locomotion through the biological barrier. In this work, we present a minimal theoretical model to investigate how heterogeneity created by a swimmer affects its own locomotion. As a generic locomotion model, we consider the swimming of a spherical squirmer in a purely viscous fluid pocket (representing the liquified or degelled region) surrounded by a Brinkman porous medium (representing the mucus gel). The use of the squirmer model enables an exact, analytical solution to this hydrodynamic problem. We obtain analytical expressions for the swimming speed, flow field, and power dissipation of the swimmer. Depending on the details of surface velocities and fluid properties, our results reveal the existence of a minimum threshold size of mucus gel that a swimmer needs to liquify in order to gain any enhancement in swimming speed. The threshold size can be as much as approximately 30% of the swimmer size. We contrast these predictions with results from previous models and highlight the significant role played by the details of surface actuations. In addition to their biological implications, these results could also inform the design of artificial microswimmers that can penetrate into biological gels for more effective drug delivery.

Wearable sweat sensors have the potential to provide continuous measurements of useful biomarkers. However, current sensors cannot accurately detect low analyte concentrations, lack multimodal sensing or are difficult to fabricate at large scale. We report an entirely laser-engraved sensor for simultaneous sweat sampling, chemical sensing and vital-sign monitoring. We demonstrate continuous detection of temperature, respiration rate and low concentrations of uric acid and tyrosine, analytes associated with diseases such as gout and metabolic disorders. We test the performance of the device in both physically trained and untrained subjects under exercise and after a protein-rich diet. We also evaluate its utility for gout monitoring in patients and healthy controls through a purine-rich meal challenge. Levels of uric acid in sweat were higher in patients with gout than in healthy individuals, and a similar trend was observed in serum.

Micro-organisms encounter heterogeneous viscous environments consisting of networks of obstacles embedded in a viscous fluid medium. In this paper we analyse the characteristics of swimming in a porous medium modelled by the Brinkman equation via a spherical squirmer model. The idealized geometry allows an analytical and exact solution of the flow surrounding a squirmer. The propulsion speed obtained agrees with previous results using the Lorentz reciprocal theorem. Our analysis extends these results to calculate the power dissipation and hence the swimming efficiency of the squirmer in a Brinkman medium. The analytical solution enables a systematic analysis of the structure of the flow surrounding the squirmer, which can be represented in terms of singularities in Brinkman flows. We also discuss the spatial decay of flows due to squirming motion in a Brinkman medium in comparison with the decay in a purely viscous fluid. The results lay the foundation for subsequent studies on hydrodynamic interactions, nutrient transport and uptake by micro-organisms in heterogeneous viscous environments.

The transport of active and passive particles plays central roles in diverse biological phenomena and engineering applications. In this paper, we present a theoretical investigation of a system consisting of an active particle and a passive particle in a confined micro-fluidic flow. The introduction of an external flow is found to induce the capture of the passive particle by the active particle via long-range hydrodynamic interactions among the particles. This hydrodynamic capture mechanism relies on an attracting stable equilibrium configuration formed by the particles, which occurs when the external flow intensity exceeds a certain threshold. We evaluate this threshold by studying the stability of the equilibrium configurations analytically and numerically. Furthermore, we study the dynamics of typical capture and non-capture events and characterize the basins of attraction of the equilibrium configurations. Our findings reveal a critical dependence of the hydrodynamic capture mechanism on the external flow intensity. Through adjusting the external flow intensity across the stability threshold, we demonstrate that the active particle can capture and release the passive particle in a controllable manner. Such a capture-and-release mechanism is desirable for biomedical applications such as the capture and release of therapeutic payloads by synthetic micro-swimmers in targeted drug delivery.

In this work we quantify the effects of surfactant transport on the deformation of a viscous drop under a DC electric field. We study how convective and diffusive transport of surfactants at drop surfaces influence the equilibrium and dynamic deformation of a leaky dielectric drop and a conducting drop. Focusing on the prolate drop shape (elongates along the electric field), we show the differences in equilibrium deformation and flow circulation between a leaky dielectric drop and a conducting drop. We quantify the drop electrodeformation via its dependence on the interior flow circulation and the dominant surfactant transport regime (characterized by the surface Péclet number Pe_{s}). For a leaky dielectric drop with dominant surfactant diffusion (Pe_{s}≪1), equator-to-pole (pole-to-equator) circulation yields smaller (larger) equilibrium deformation with increasing surfactant coverage, compared to a clean drop. However, when convection dominates (Pe_{s}≫1), the equilibrium drop deformation increases (decreases) with larger surfactant coverage for equator-to-pole (pole-to-equator) circulation. Larger equilibrium drop deformation is found for a leaky dielectric drop than a conducting drop when the interior flow is from equator to pole. For an interior flow from pole to equator, we identify cases where larger deformation is found for a conducting interior fluid. Finally, we study the effect of the surfactant transport on the dynamic evolution of drop shape. We found the drop undergoes an overshoot in the early deformation phase, before settling to its equilibrium shape-similar to the overshoot observed for unsteady Stokes flow.

Droplet microfluidics has the ability to greatly increase the throughput of screening and sorting of enzymes by carrying reagents in picoliter droplets flowing in inert oils. It was found with the use of a specific surfactant, the interfacial tension of droplets can be very sensitive to droplet pH. This enables the sorting of droplets of different pH when confined droplets encounter a microfabricated trench. The device can be extended to sort enzymes, as a large number of enzymatic reactions lead to the production of an acidic or basic product and a concurrent change in solution pH. The progress of an enzymatic reaction is tracked from the position of a flowing train of droplets. We demonstrate the sorting of esterase isoenzymes based on their enzymatic activity. This label-free technology, that we dub droplet sorting by interfacial tension (SIFT), requires no active components and would have applications for enzyme sorting in high-throughput applications that include enzyme screening and directed evolution of enzymes.

Reinforcement learning control methods can impart robots with the ability to discover effective behavior, reducing their modeling and sensing requirements, and enabling their ability to adapt to environmental changes. However, it remains challenging for a robot to achieve navigation in confined and dynamic environments, which are characteristic of a broad range of biomedical applications, such as endoscopy with ingestible electronics. Herein, a compact, 3D-printed three-linked-sphere robot synergistically integrated with a reinforcement learning algorithm that can perform adaptable, autonomous crawling in a confined channel is demonstrated. The scalable robot consists of three equally sized spheres that are linearly coupled, in which the extension and contraction in specific sequences dictate its navigation. The ability to achieve bidirectional locomotion across frictional surfaces in open and confined spaces without prior knowledge of the environment is also demonstrated. The synergistic integration of a highly scalable robotic apparatus and the model-free reinforcement learning control strategy can enable autonomous navigation in a broad range of dynamic and confined environments. This capability can enable sensing, imaging, and surgical processes in previously inaccessible confined environments in the human body.

There is growing interest in the development of artificial microscopic machines that can perform complex maneuvers like swimming microorganisms for potential biomedical applications. At the microscopic scales, the dominance of viscous over inertial forces imposes stringent constraints on locomotion. In the absence of inertia, Purcell first proposed an elegant way to generate net translation using kinematically irreversible motions [E. M. Purcell, “Life at low Reynolds number,” Am. J. Phys. 45, 3–11 (1977)]. In addition to net translation, a more recent prototype known as Purcell's “rotator” has been proposed in Dreyfus et al. [“Purcell's “rotator”: Mechanical rotation at low Reynolds number,” Eur. Phys. J. B 47, 161–164 (2005)] as a mechanical implementation of net rotation at low Reynolds numbers. These ingenious designs rely on knowledge of the surrounding environment and the physics of locomotion within the environment, which may be incomplete or unclear in more complex scenarios. More recently, reinforcement learning has been used as an alternative approach to enable a machine to learn effective locomotory gaits for net translation based on its interaction with the surroundings. In this work, we demonstrate the use of reinforcement learning to generate net mechanical rotation at low Reynolds numbers without requiring prior knowledge of locomotion. For a three-sphere configuration, the reinforcement learning recovers the strategy proposed by Dreyfus et al. As the number of spheres increases, multiple effective rotational strategies emerge from the learning process. However, given sufficiently long learning processes, all machines considered in this work converge to a single type of rotational policies that consist of traveling waves of actuation, suggesting its optimality of the strategy in generating net rotation at low Reynolds numbers.

Mechanosensation is an important process in biological fluid–structure interaction. To understand the biophysics underlying mechanosensation, it is essential to quantify the correlation between membrane deformation, membrane tension, external fluid shear stress, and conformation of mechanosensitive (MS) channels. Smoothed dissipative particle dynamics (SDPD) simulations of vesicle/cell in three types of flow configurations are conducted to calculate the tension in lipid membrane due to fluid shear stress from the surrounding viscous flow. In combination with a simple continuum model for an MS channel, SDPD simulation results suggest that shearing adhered vesicles/cells is more effective to induce membrane tension sufficient to stretch MS channels open than a free shear flow or a constrictive channel flow. In addition, we incorporate the bilayer–cytoskeletal interaction in a two-component model to probe the effects of a cytoskeletal network on the gating of MS channels.

Micro-organisms and artificial microswimmers often move in biological fluids displaying complex rheological behaviors, including viscoelasticity and shear-thinning viscosity. A comprehensive understanding of the effectiveness of different swimming gaits in various types of complex fluids remains elusive. The squirmer model has been commonly used to represent different types of swimmers and probe the effects of different types of complex rheology on locomotion. While many studies focused only on squirmers with surface velocities in the polar direction, a recent study has revealed that a squirmer with swirling motion can swim faster in a viscoelastic fluid than in Newtonian fluids [Binagia et al., J. Fluid Mech. 900, A4, (2020)]. Here, we consider a similar setup but focus on the sole effect due to shear-thinning viscosity. We use asymptotic analysis and numerical simulations to examine how the swirling flow affects the swimming performance of a squirmer in a shear-thinning but inelastic fluid described by the Carreau constitutive equation. Our results show that the swirling flow can either increase or decrease the speed of the squirmer depending on the Carreau number. In contrast to swimming in a viscoelastic fluid, the speed of a swirling squirmer in a shear-thinning fluid does not go beyond the Newtonian value in a wide range of parameters considered. We also elucidate how the coupling of the azimuthal flow with shear-thinning viscosity can produce the rotational motion of a swirling pusher or puller.

Rapid and low-cost pathogen diagnostic approaches are critical for clinical decision-making procedures. Cultivating bacteria often takes days to identify pathogens and provide antimicrobial susceptibilities. The delay in diagnosis may result in compromised treatment and inappropriate antibiotic use. Over the past decades, molecular-based techniques have significantly shortened pathogen identification turnaround time with high accuracy. However, these assays often use complex fluorescent labeling and nucleic acid amplification processes, which limit their use in resource-limited settings. In this work, we demonstrate a wash-free molecular agglutination assay with a straightforward mixing and incubation step that significantly simplifies procedures of molecular testing. By targeting the 16S rRNA gene of pathogens, we perform a rapid pathogen identification within 30 min on a dark-field imaging microfluidic cytometry platform. The dark-field images with low background noise can be obtained using a narrow beam scanning technique with off-the-shelf complementary metal oxide semiconductor (CMOS) imagers such as smartphone cameras. We utilize a machine learning algorithm to deconvolute topological features of agglutinated clusters and thus quantify the abundance of bacteria. Consequently, we unambiguously distinguish Escherichia coli positive from other E. coli negative among 50 clinical urinary tract infection samples with 96% sensitivity and 100% specificity. Furthermore, we also apply this quantitative detection approach to achieve rapid antimicrobial susceptibility testing within 3 h. This work exhibits easy-to-use protocols, high sensitivity, and short turnaround time for point-of-care testing uses., A novel integration of emerging techniques of machine learning and narrow beam scanning into molecular agglutination assays to develop a rapid, low-cost pathogen detection platform is reported.

Synthetic microswimmers show great promise in biomedical applications such as drug delivery and microsurgery. Their locomotion, however, is subject to stringent constraints due to the dominance of viscous over inertial forces at low Reynolds number (Re) in the microscopic world. Furthermore, locomotory gaits designed for one medium may become ineffective in a different medium. Successful biomedical applications of synthetic microswimmers rely on their ability to traverse biological environments with vastly different properties. Here we leverage the prowess of machine learning to present an alternative approach to designing low Re swimmers. Instead of specifying any locomotory gaits \textit{a priori}, here a swimmer develops its own propulsion strategy based on its interactions with the surrounding medium via reinforcement learning. This self-learning capability enables the swimmer to modify its propulsion strategy in response to different environments. We illustrate this new approach using a minimal example that integrates a standard reinforcement learning algorithm ($Q$-learning) into the locomotion of a swimmer consisting of an assembly of spheres connected by extensible rods. We showcase theoretically that this first self-learning swimmer can recover a previously known propulsion strategy without prior knowledge in low Re locomotion, identify more effective locomotory gaits when the number of spheres increases, and adapt its locomotory gaits in different media. These results represent initial steps towards the design of a new class of self-learning, adaptive (or "smart") swimmers with robust locomotive capabilities to traverse complex biological environments.

A multiscale continuum model is constructed for a mechanosensitive (MS) channel gated by tension in a lipid bilayer membrane under stresses due to fluid flows. We illustrate that for typical physiological conditions vesicle hydrodynamics driven by a fluid flow may render the membrane tension sufficiently large to gate a MS channel open. In particular, we focus on the dynamic opening/closing of a MS channel in a vesicle membrane under a planar shear flow and a pressure-driven flow across a constriction channel. Our modeling and numerical simulation results quantify the critical flow strength or flow channel geometry for intracellular transport through a MS channel. In particular, we determine the percentage of MS channels that are open or closed as a function of the relevant measure of flow strength. The modeling and simulation results imply that for fluid flows that are physiologically relevant and realizable in microfluidic configurations stress-induced intracellular transport across the lipid membrane can be achieved by the gating of reconstituted MS channels, which can be useful for designing drug delivery in medical therapy and understanding complicated mechanotransduction.

Biological locomotion in nature is often achieved by the interaction between a flexible body and its surrounding medium. The interaction of a flexible body with granular media is less understood compared with viscous fluids partially due to its complex rheological properties. In this work we explore the effect of flexibility on granular propulsion by considering a simple mechanical model where a rigid rod is connected to a torsional spring that is under a displacement actuation using a granular resistive force theory. Through a combined numerical and asymptotic investigation, we characterize the propulsive dynamics of such a flexible flapper in relation to the actuation amplitude and spring stiffness and compare these dynamics with those observed in a viscous fluid. In addition, we demonstrate that the maximum possible propulsive force can be obtained in the steady propulsion limit with a finite spring stiffness and large actuation amplitude. These results may apply to the development of synthetic locomotive systems that exploit flexibility to move through complex terrestrial media., 9 pages, 5 figures

At low Reynolds numbers the locomotive capability of a body can be dramatically hindered by the absence of inertia. In this work, we show how propulsive performance in this regime can be significantly enhanced by employing spatially varying flexibility. As a prototypical example, we consider the propulsive thrust generated by a filament periodically driven at one end. The rigid case leads to zero propulsion, as so constrained by Purcell's scallop theorem, while for uniform filaments there exists a bending stiffness maximizing the propulsive force at a given frequency; here we demonstrate explicitly how considerable further improvement (greater than 37% enhancement compared with the optimal uniform stiffness) can be achieved by simply varying the stiffness along the filament. The optimal flexibility distribution is strongly configuration-dependent: while increasing the flexibility towards the tail-end enhances the propulsion of a clamped filament, for a hinged filament decreasing the flexibility towards the tail-end is instead favorable. The results reveal new design principles for maximizing propulsion at low Reynolds numbers, potentially useful for developing synthetic micro-swimmers requiring large propulsive force for various biomedical applications., 5 figures

Micro-organisms expend energy moving through complex media. While propulsion speed is an important property of locomotion, efficiency is another factor that may determine the swimming gait adopted by a micro-organism in order to locomote in an energetically favorable manner. The efficiency of swimming in a Newtonian fluid is well characterized for different biological and artificial swimmers. However, these swimmers often encounter biological fluids displaying shear-thinning viscosities. Little is known about how this nonlinear rheology influences the efficiency of locomotion. Does the shear-thinning rheology render swimming more efficient or less? How does the swimming efficiency depend on the propulsion mechanism of a swimmer and rheological properties of the surrounding shear-thinning fluid? In this work, we address these fundamental questions on the efficiency of locomotion in a shear-thinning fluid by considering the squirmer model as a general locomotion model to represent different types of swimmers. Our analysis reveals how the choice of surface velocity distribution on a squirmer may reduce or enhance the swimming efficiency. We determine optimal shear rates at which the swimming efficiency can be substantially enhanced com- pared with the Newtonian case. The non-trivial variations of swimming efficiency prompt questions on how micro-organisms may tune their swimming gaits to exploit the shear-thinning rheology. The findings also provide insights into how artificial swimmers should be designed to move through complex media efficiently.

The motion of a spherical drop with a bulk-insoluble surfactant immersed in a background flow in the limits of low surface Péclet number and low Reynolds number is investigated. We develop a reciprocal theorem that applies to any prescribed background flow and provide a specific example of an unbounded Poiseuille flow. Analytical formulas for the migration velocity of the drop are obtained perturbatively in powers of the surface Péclet number. We show that the redistribution of surfactant due to the background flow acts to retard the motion of the drop, with the magnitude of this slip velocity being independent of the drop’s position in the Poiseuille flow. Moreover, a surfactant-induced cross-streamline migration of the drop occurs towards the centre of the Poiseuille flow, with its magnitude depending linearly on the distance of the drop from the centre of the Poiseuille flow.

Rapid field conversion of chemical weapons into non-toxic products is one of the most challenging tasks in weapons of mass destruction (WMD) science. This is particularly the case for eliminating stockpiles of chemical warfare agents (CWAs) in remote storage field locations, where the use of large quantities of decontaminating reagents, long reaction times, and controlled mechanical agitation is impossible or undesired. New efficient “clean” technologies and (bio)chemical processes are thus sought for detoxifying stored agents, counteracting nerve-agent attacks, and decommissioning chemical weapons. Environmentally friendly solutions of hydrogen peroxide, combined with suitable activators (e.g., bicarbonate), have been shown to be extremely useful for decontaminating a broad spectrum of CWAs to yield nontoxic products. These peroxide-based systems, which rely on the in situ generation of OOH nucleophiles, have recently replaced chlorine-based bleaching processes, which produce undesirable products, and have thus led to effective decontamination of the chemical agents GB (Sarin, isopropyl methylphosphonofluoridate), VX ((S)-[2-(diisopropylamino)ethyl] O-ethyl methylphosphonothioate), GD (Soman, pinacolyl methylphosphonofluoridate), and HD (sulfur mustard). Yet, such an oxidative treatment commonly requires high peroxide concentrations (20–30%; approaching a stoichiometry of 1:50), along with prolonged operation and/or mechanical agitation. Such reaction conditions are not suitable or not desired for eliminating stockpiles of CWAs in remote field settings or hostile storage locations, as large quantities of the reagents may not be transportable on military aircrafts and require special packaging and handling. The efficient elimination of chemical-weapon stockpiles in field locations thus remains a major challenge to the chemistry and defense communities. Herein, we describe a powerful strategy that is based on self-propelled micromotors, for a high-yielding accelerated oxidative decontamination of chemical threats using low peroxide levels and no external agitation. Functionalized synthetic micromotors have recently demonstrated remarkable capabilities in terms of isolation and transport for diverse biomedical and environmental applications, but not in connection to increasing the yield and speed of chemical reactions. The new motor-based method relies on the use of peroxide-driven microtubular engines for the efficient selfmixing of a remediation solution, which dramatically accelerates the decontamination process. Fluid mixing is extremely important for enhancing the yield and speed of a wide range of chemical processes, including decontamination reactions, where quiescent conditions lead to low reaction efficiency and long operations. The observed mixing, which is induced by the peroxide-driven micromotor, is analogous to that reported for the motility of E. coli bacteria, where a large-scale collective motion has been shown to enhance diffusion processes. Enhanced diffusion of passive tracers has also been observed in the presence of catalytic nanowire motors. Although the new micromotor strategy presented herein was applied to the accelerated, high-yielding, and simplified decontamination of organophosphate (OP) nerve agents, the concept could have broad implications for enhancing the efficiency and speed of a wide range of chemical processes in the absence of external agitation. The concept of the micromotor/peroxide-based decontamination of chemical threats is illustrated in Figure 1. This new strategy relies on micromotors without mechanical stirring (Figure 1A). A known number of micromotors were placed in a nerve-agent-contaminated solution, along with hydrogen peroxide (used as the oxidizing agent as well as the micromotor fuel), the peroxide activator (NaHCO3 or NaOH), and the surfactant sodium cholate (NaCh), which was essential for bubble generation. The oxidative conversion of the OP nerve agent into para-nitrophenol (p-NP) was achieved under mild quiescent conditions that involve the in situ generation of OOH nucleophiles with no external stirring (Figure 1B). The decrease in concentration of the OP [*] Dr. J. Orozco, G. Cheng, D. Vilela, Dr. S. Sattayasamitsathit, Prof. R. Vazquez-Duhalt, Dr. G. Vald s-Ram rez, Dr. O. S. Pak, Prof. J. Wang Departments of Nanoengineering and Mechanical Engineering University of California San Diego La Jolla, CA 92093 (USA) E-mail: josephwang@ucsd.edu G. Cheng, Prof. C. Kan Tsinghua University, Beijing, 100084 (China) D. Vilela, Prof. A. Escarpa University of Alcal 28871 Alcal de Henares (Spain)

We study the two-dimensional Brownian dynamics of an ellipsoidal paramagnetic microswimmer moving at a low Reynolds number and subject to a magnetic field. Its corresponding mean-square displacement, showing the effect of a particles's shape, activity, and magnetic field on the microswimmer's diffusion, is analytically obtained. Comparison between analytical and computational results shows good agreement. In addition, the effect of self-propulsion on the transition time from anisotropic to isotropic diffusion of the ellipse is investigated.

We investigate the gating mechanism of large conductance mechanosensitive channels (MscLs) on cellular membranes and vesicles using an integrated approach including theoretical modeling, multiscale simulations and microfluidics experiments. At the channel level, we recently developed a theoretical model to study the MscL gating in vesicles exposed to physiological fluid flows, demonstrating the possibility of gating MscL via flow-generated membrane tension (Pak, et al, PNAS, 112:9822-7, 2015). At the cellular level, membrane tension under different flow conditions is calculated using a 3D whole-cell model based on dissipative particle dynamics (DPD). The simulated tension is passed to the MscL channel model to predict the MscL gating. The system will also be studied with microfluidics experiments including micropipette array aspiration, constricted tube flow and shear flow for comparison with results from theoretical modeling. The results provide guidance for future experiments in inducing MscL opening for intracellular transport.

Experimental studies have demonstrated that spermatozoa synchronize their flagella when swimming in close proximity. In a Newtonian fluid, it was shown theoretically that such synchronization arises passively due to hydrodynamic forces between the two swimmers if their waveforms exhibit a front–back geometrical asymmetry. Motivated by the fact that most biological fluids possess a polymeric microstructure, here we address synchronization in a viscoelastic fluid analytically. Using a two-dimensional infinite sheet model, we show that the presence of polymeric stresses removes the geometrical asymmetry constraint and therefore even symmetric swimmers synchronize. Such synchronization occurs on asymptotically faster time scales than in a Newtonian fluid, and the swimmers are seen to be driven into a stable in-phase conformation minimizing the energy dissipated in the surrounding fluid.

Small-scale locomotion plays an important role in biology. Different modelling approaches have been proposed in the past. The simplest model is an infinite inextensible two-dimensional waving sheet, originally introduced by Taylor, which serves as an idealized geometrical model for both spermatozoa locomotion and ciliary transport in Stokes flow. Here, we complement classic steady-state calculations by deriving the transient low-Reynolds number swimming speed of such a waving sheet when starting from rest (small-amplitude initial-value problem). We also determine the transient fluid flow in the ‘pumping’ setup where the sheet is not free to move but instead generates a net fluid flow around it. The time scales for these two problems, which in general govern transient effects in transport and locomotion at low Reynolds numbers, are also derived using physical arguments.