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Register a new userDesigning phoretic micro- and nano-swimmers
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Small objects can swim by generating around them fields or gradients which in turn induce fluid motion past their surface by phoretic surface effects. We quantify for arbitrary swimmer shapes and surface patterns, how efficient swimming requires both surface ``activity to generate the fields, and surface ``phoretic mobility. We show in particular that (i) swimming requires symmetry breaking in either or both of the patterns of activity and ``mobility, and (ii) for a given geometrical shape and surface pattern, the swimming velocity is size-independent. In addition, for given available surface properties, our calculation framework provides a guide for optimizing the design of swimmers.
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Surface interactions provide a class of mechanisms which can be employed for propulsion of micro- and nanometer sized particles. We investigate the related efficiency of externally and self-propelled swimmers. A general scaling relation is derived showing that only swimmers whose size is comparable to, or smaller than, the interaction range can have appreciable efficiency. An upper bound for efficiency at maximum power is 1/2. Numerical calculations for the case of diffusiophoresis are found to be in good agreement with analytical expressions for the efficiency.
We report an experimental study on ion-exchange based modular micro-swimmers in low-salt water. Cationic ion-exchange particles and passive cargo particles assemble into self-propelling complexes, showing self-propulsion at speeds of several microns per second over extended distances and times. We quantify the assembly and speed of the complexes for different combinations of ion exchange particles and cargo particles, substrate types, salt types and concentrations, and cell geometries. Irrespective of experimental boundary conditions, we observe a regular development of the assembly shape with increasing number of cargo. Moreover, the swimming speed increases stepwise upon increasing the number of cargo and then saturates at a maximum speed, indicating an active role of cargo in modular swimming. We propose a geometric model of self-assembly to describe the experimental observations in a qualitative way. Our study also provides some constraints for future theoretical modelling and simulation.
Cooperation is vital for the survival of a swarm$^1$. Large scale cooperation allows murmuring starlings to outmaneuver preying falcons$^2$, shoaling sardines to outsmart sea lions$^3$, and homo sapiens to outlive their Pleistocene peers$^4$. On the micron-scale, bacterial colonies show excellent resilience thanks to the individuals ability to cooperate even when densely packed, mitigating their internal flow pattern to mix nutrients, fence the immune system, and resist antibiotics$^{5-14}$. Production of an artificial swarm on the micro-scale faces a serious challenge $frac{;;}{;;}$ while an individual bacterium has an evolutionary-forged internal machinery to produce propulsion, until now, artificial micro-swimmers relied on the precise chemical composition of their environment to directly fuel their drive$^{14-23}$. When crowded, artificial micro-swimmers compete locally for a finite fuel supply, quenching each others activity at their greatest propensity for cooperation. Here we introduce an artificial micro-swimmer that consumes no chemical fuel and is driven solely by light. We couple a light absorbing particle to a fluid droplet, forming a colloidal chimera that transforms light energy into propulsive thermo-capillary action. The swimmers internal drive allows them to operate and remain active for a long duration (days) and their effective repulsive interaction allows for a high density fluid phase. We find that above a critical concentration, swimmers form a long lived crowded state that displays internal dynamics. When passive particles are introduced, the dense swimmer phase can re-arrange and spontaneously corral the passive particles. We derive a geometrical, depletion-like condition for corralling by identifying the role the passive particles play in controlling the effective concentration of the micro-swimmers.
Efficient navigation and precise localization of Brownian micro/nano self-propelled motor particles within complex landscapes could enable future high-tech applications involving for example drug delivery, precision surgery, oil recovery, and environmental remediation. Here we employ a model-free deep reinforcement learning algorithm based on bio-inspired neural networks to enable different types of micro/nano motors to be continuously controlled to carry out complex navigation and localization tasks. Micro/nano motors with either tunable self-propelling speeds or orientations or both, are found to exhibit strikingly different dynamics. In particular, distinct control strategies are required to achieve effective navigation in free space and obstacle environments, as well as under time constraints. Our findings provide fundamental insights into active dynamics of Brownian particles controlled using artificial intelligence and could guide the design of motor and robot control systems with diverse application requirements.
Microstructure, phase transitions, electrical conductivity, and optical and electrooptical properties of multiwalled carbon nanotubes (NTs), dispersed in the cholesteric liquid crystal (cholesteryl oleyl carbonate, COC), nematic 5CB and their mixtures, were studied in the temperature range between 255 K and 363 K. The relative concentration X=COC/(COC+5CB)was varied within 0.0-1.0. The concentration $C_p$ of NTs was varied within 0.01-5% wt. The value of X affected agglomeration and stability of NTs inside COC+5CB. High-quality dispersion, exfoliation, and stabilization of the NTs were observed in COC solvent (good solvent). From the other side, the aggregation of NTs was very pronounced in nematic 5CB solvent (bad solvent). The dispersing quality of solvent influenced the percolation concentration $C_p$, corresponding to transition between the low conductive and high conductive states: e.g., percolation was observed at $C_p=1%$ and $C_p=0.1%$ for pure COC and 5CB, respectively. The effects of thermal pre-history on the heating-cooling hysteretic behavior of electrical conductivity were studied. The mechanism of dispersion of NTs in COC+5CB mixtures is discussed. Utilization of the mixtures of good and bad solvents allowed fine regulation of the dispersion, stability and electrical conductivity of LC+NTs composites. The mixtures of COC and 5CB were found to be promising for application as functional media with controllable useful chiral and electrophysical properties.
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