Collective response of microrobotic swarms to external threats published in New Journal of Physics

A swarm of microrobots, consist of active Janus colloids (middle right, not to scale), can form stationary swirl (upper) and respond to a threat as a whole (lower) when each individual follows cohesive “social rules”. Such rules are inspired by living animals and enable the swarm collective benefits, e.g. enhanced robustness of the response. (Image by C-J Chen.)
Collective response of microrobotic swarms to external threats

Chun-Jen Chen and Clemens Bechinger
New J. Phys. 24 033001 (2022)
doi: 10.1088/1367-2630/ac5374
repository: KOPS:56911

Many animal species organize within groups to achieve advantages compared to being isolated. Such advantages can be found e.g. in collective responses which are less prone to individual failures or noise and thus provide better group performance. Inspired by social animals, here we demonstrate with a swarm of microrobots made from programmable active colloidal particles (APs) that their escape from a hazardous area can originate from a cooperative group formation. As a consequence, the escape efficiency remains almost unchanged even when half of the APs are not responding to the threat. Our results not only confirm that incomplete or missing individual information in robotic swarms can be compensated by other group members but also suggest strategies to increase the responsiveness and fault-tolerance of robotic swarms when performing tasks in complex environments.

Press release at Universität Konstanz website:
How animal swarms respond to threats: With the help of microrobots, Konstanz physicists decode how swarms of animals respond effectively to danger [in English]

Brownian particles driven by spatially periodic noise published in EPJE

Brownian particles driven by spatially periodic noise
Davide Breoni, Ralf Blossey, Hartmut Löwen
The European Physical Journal E 45, 18 (2022)
arXiv: 2111.10220
DOI:10.1140/epje/s10189-022-00176-4

We discuss the dynamics of a Brownian particle under the influence of a spatially periodic noise strength in one dimension using analytical theory and computer simulations. In the absence of a deterministic force, the Langevin equation can be integrated formally exactly. We determine the short- and long-time behaviour of the mean displacement (MD) and mean-squared displacement (MSD). In particular we find a very slow dynamics for the mean displacement, scaling as t^(-1/2) with time t. Placed under an additional external periodic force near the critical tilt value we compute the stationary current obtained from the corresponding Fokker-Planck equation and identify an essential singularity if the minimum of the noise strength is zero. Finally, in order to further elucidate the effect of the random periodic driving on the diffusion process, we introduce a phase factor in the spatial noise with respect to the external periodic force and identify the value of the phase shift for which the random force exerts its strongest effect on the long-time drift velocity and diffusion coefficient.

A platform for stop flow gradient generation to investigate chemotaxis published in Angewandte Chemie

A controlled gradient of hydrogen peroxide is generated in a microfluidic chip where a precise pressure retroactive loop prevents any external flow to interfere with the chemotaxis response of catalytic microswimmers. (Image by A. Nsamela.)
A platform for stop flow gradient generation to investigate chemotaxis
Z. Xiao, A. Nsamela, B. Garlan, and J. Simmchen
Angew. Chemie Int. Ed., Feb. 2022
chemRxiv: 10.26434/chemrxiv-2021-sxqm1
DOI: 10.1002/anie.202117768

The ability of artificial microswimmers to respond to external stimuli and the mechanistical details of their origins belong to the most disputed challenges in interdisciplinary science. Therein, the creation of chemical gradients is technically challenging, because they quickly level out due to diffusion. Inspired by pivotal stopped ow experiments in chemical kinetics, we show that microfluidics gradient generation combined with a pressure feedback loop for precisely controlling the stop of the flows, can enable us to study mechanistical details of chemotaxis of artificial Janus micromotors, based on a catalytic reaction. We find that these copper Janus particles display a chemotactic motion along the concentration gradient in both, positive and negative direction and we demonstrate the mechanical reaction of the particles to unbalanced drag forces, explaining this behaviour.

Raman tweezers for tire and road wear micro- and nanoparticles analysis published in Environmental Science: Nano

Raman Tweezers are used to detect tires and road wear particles in water. We analyze samples collected from a brake test platform, highlighting the presence of car tires and brake particles debris with sub-micrometric dimensions. (Featuring work from Dr Pietro G. Gucciardi, Prof Giovanni Volpe, and Dr Fabienne Lagarde).
Raman tweezers for tire and road wear micro- and nanoparticles analysis

R. GillibertA. MagazzùA. CallegariD. Bronte-CirizaA. FotiM. G. DonatoO. M. MaragòG. VolpeM. L. de La ChapelleF. Lagarde and P. G. Gucciardi.

Environmental Science: Nano (2022) doi: 10.1039/D1EN00553G

Abstract:

Tire and road wear particles (TRWP) are non-exhaust particulate matter generated by road transport means during the mechanical abrasion of tires, brakes and roads. TRWP accumulate on the roadsides and are transported into the aquatic ecosystem during stormwater runoffs. Due to their size (sub-millimetric) and rubber content (elastomers), TRWP are considered microplastics (MPs). While the amount of the MPs polluting the water ecosystem with sizes from ∼5 μm to more than 100 μm is known, the fraction of smaller particles is unknown due to the technological gap in the detection and analysis of <5 μm MPs. Here we show that Raman tweezers, a combination of optical tweezers and Raman spectroscopy, can be used to trap and chemically analyze individual TRWPs in a liquid environment, down to the sub-micrometric scale. Using tire particles mechanically grinded from aged car tires in water solutions, we show that it is possible to optically trap individual sub-micron particles, in a so-called 2D trapping configuration, and acquire their Raman spectrum in few tens of seconds. The analysis is then extended to samples collected from a brake test platform, where we highlight the presence of sub-micrometric agglomerates of rubber and brake debris, thanks to the presence of additional spectral features other than carbon. Our results show the potential of Raman tweezers in environmental pollution analysis and highlight the formation of nanosized TRWP during wear.

Microfluidics for Microswimmers, a tutorial review published in Small

Illustration of the synergies between microfluidics and microswimmers described in this review: from the fabrication, to the design of environments and envisioned applications. (Image by A. Nsamela.)
Microfluidics for Microswimmers: Engineering Novel Swimmers and Constructing Swimming Lanes on the Microscale, a Tutorial Review

Priyanka Sharan, Audrey Nsamela, Sasha Cai Lesher-Pérez and Juliane Simmchen Small, 2007403 (2021) doi: 10.1002/smll.202007403

Abstract: This paper provides an updated review of recent advances in microfluidics applied to artificial and biohybrid microswimmers. Sharing the common regime of low Reynolds number, the two fields have been brought together to take advantage of the fluid characteristics at the microscale, benefitting microswimmer research multifold. First, microfluidics offer simple and relatively low‐cost devices for high‐fidelity production of microswimmers made of organic and inorganic materials in a variety of shapes and sizes. Microscale confinement and the corresponding fluid properties have demonstrated differential microswimmer behaviors in microchannels or in the presence of various types of physical or chemical stimuli. Custom environments to study these behaviors have been designed in large part with the help of microfluidics. Evaluating microswimmers in increasingly complex lab environments such as microfluidic systems can ensure more effective implementation for in‐field applications. The benefits of microfluidics for the fabrication and evaluation of microswimmers are balanced by the potential use of microswimmers for sample manipulation and processing in microfluidic systems, a large obstacle in diagnostic and other testing platforms. In this review various ways in which these two complementary technology fields will enhance microswimmer development and implementation in various fields are introduced.

Effect of viscosity on microswimmers: a comparative study published in ChemNanoMat

Illustration of the four types of microswimmers used in the viscosity study. (Image by A. Nsamela.)
Effect of viscosity on microswimmers: a comparative study

Audrey Nsamela, Priyanka Sharan, Aidee Garcia-Zintzun, Sandra Heckel, Purnesh Chattopadhyay, Linlin Wang, Martin Wittmann, Thomas Gemming, James Saenz and Juliane Simmchen ChemNanoMat (2021) doi: 10.1002/cnma.202100119

Abstract: Although many biological fluids like blood and mucus exhibit high viscosities, there are still many open questions concerning the swimming behavior of microswimmers in highly viscous media, limiting research to idealized laboratory conditions instead of application‐oriented scenarios. Here, we analyze the effect of viscosity on the swimming speed and motion pattern of four kinds of microswimmers of different sizes which move by contrasting propulsion mechanisms: two biological swimmers (bovine sperm cells and Bacillus subtilis bacteria) which move by different bending patterns of their flagellaand two artificial swimmers with catalytic propulsion mechanisms (alginate microtubes and Janus Pt@SiO 2 spherical microparticles). Experiments consider two different media (glycerol and methylcellulose) with increasing viscosity, but also the impact of surface tension, catalyst activity and diffusion coefficients are discussed and evaluated.

Morphology of active deformable 3D droplets published in Physical Review X

3D droplets composed of active matter change their shape in response to a continuous influx of energy. Active droplets display an unprecedented range of complex morphologies, from cup-shaped droplet invagination, run-and-tumble motion or surface wrinkles caused by contractile activity, to the continuous formation and retraction of finger-like protrusions driven by extensile activity.
Morphology of active deformable 3D droplets
Liam J. Ruske, Julia M. Yeomans
Phys. Rev. X 11, 021001 (2021)

Abstract:
We numerically investigate the morphology and disclination line dynamics of active nematic droplets in three dimensions. Although our model incorporates only the simplest possible form of achiral active stress, active nematic droplets display an unprecedented range of complex morphologies. For extensile activity, fingerlike protrusions grow at points where disclination lines intersect the droplet surface. For contractile activity, however, the activity field drives cup-shaped droplet invagination, run-and-tumble motion, or the formation of surface wrinkles. This diversity of behavior is explained in terms of an interplay between active anchoring, active flows, and the dynamics of the motile disclination lines. We discuss our findings in the light of biological processes such as morphogenesis, collective cancer invasion, and the shape control of biomembranes, suggesting that some biological systems may share the same underlying mechanisms as active nematic droplets.

Optical tweezers in a dusty universe published in The European Physical Journal Plus

Pictorial representation of space tweezers, space applications of optical tweezers. Interplanetary or planetary dust can be collected and investigated directly in situ (open space or extraterrestrial surfaces). The inset represents a closeup of a grain of interplanetary dust trapped by a single-beam optical tweezers. (Image by Alessandro Magazzù)
Optical tweezers in a dusty universe
P. Polimeno, A. Magazzù, M. A. Iatì, R. Saija, L. Folco, D. Bronte Ciriza, M. G. Donato, A. Foti, P. G. Gucciardi, A. Saidi, C. Cecchi-Pestellini, A. Jimenez Escobar, E. Ammannito, G. Sindoni, I. Bertini, V. Della Corte, L. Inno, A. Ciaravella, A. Rotundi & O. M. Maragò
Eur. Phys. J. Plus 136, 339 (2021)
doi: 10.1140/epjp/s13360-021-01316-z

Abstract:
Optical tweezers are powerful tools based on focused laser beams. They are able to trap, manipulate, and investigate a wide range of microscopic and nanoscopic particles in different media, such as liquids, air, and vacuum. Key applications of this contactless technique have been developed in many fields. Despite this progress, optical trapping applications to planetary exploration are still to be developed. Here we describe how optical tweezers can be used to trap and characterize extraterrestrial particulate matter. In particular, we exploit light scattering theory in the T-matrix formalism to calculate radiation pressure and optical trapping properties of a variety of complex particles of astrophysical interest. Our results open perspectives in the investigation of extraterrestrial particles on our planet, in controlled laboratory experiments, aiming for space tweezers applications: optical tweezers used to trap and characterize dust particles in space or on planetary bodies surface.

Improving epidemic testing and containment strategies using machine learning accepted in Machine Learning: Science and Technology

Comparison of different evolution regimes of disease spreading: free evolution (bottom left half) vs network strategy (top right half). Image by L. Natali.
Improving epidemic testing and containment strategies using machine learning
Laura Natali, Saga Helgadottir, Onofrio M. Maragò, Giovanni Volpe
Machine Learning: Science and Technology (2021)
doi: 10.1088/2632-2153/abf0f7
arXiv: 2011.11717

Containment of epidemic outbreaks entails great societal and economic costs. Cost-effective containment strategies rely on efficiently identifying infected individuals, making the best possible use of the available testing resources. Therefore, quickly identifying the optimal testing strategy is of critical importance. Here, we demonstrate that machine learning can be used to identify which individuals are most beneficial to test, automatically and dynamically adapting the testing strategy to the characteristics of the disease outbreak. Specifically, we simulate an outbreak using the archetypal susceptible-infectious-recovered (SIR) model and we use data about the first confirmed cases to train a neural network that learns to make predictions about the rest of the population. Using these prediction, we manage to contain the outbreak more effectively and more quickly than with standard approaches. Furthermore, we demonstrate how this method can be used also when there is a possibility of reinfection (SIRS model) to efficiently eradicate an endemic disease.

Active noise-driven particles under space-dependent friction in one dimension on arXiv

Sketch of the confining potential U(x) = κ|x|, a linear friction gradient γ(x) = γ0+γ1|x| in arbitrary units. The particle, shown by a blue dot on the x-axis, is activated by noise (indicated in red), under the influence of the potential and the friction gradient. Image by D. Breoni.
Active noise-driven particles under space-dependent friction in one dimension

Davide Breoni, Ralf Blossey, Hartmut Löwen
arxiv: 2102.09944

Abstract: We study a Langevin equation describing the stochastic motion of a particle in one dimension with coordinate x, which is simultaneously exposed to a space-dependent friction coefficient γ (x), a confining potential U(x) and non-equilibrium (i.e., active) noise. Specically, we consider frictions γ (x) = γ0 + γ1|x|p and potentials U(x) ∝ |x|p with exponents p = 1; 2 and n = 0; 1; 2. We provide analytical and numerical results for the particle dynamics for short times and the stationary
probability density functions (PDFs) for long times. The short-time behaviour displays diffusive and ballistic regimes while the stationary PDFs display unique characteristic features depending on the exponent values (p; n). The PDFs interpolate between Laplacian, Gaussian and bimodal distributions, whereby a change between these different behaviours can be achieved by a tuning of the friction strengths ratio
γ0 / γ1. Our model is relevant for molecular motors moving on a
one-dimensional track and can also be realized for confined self-propelled colloidal particles.