Catching fish with a fishing net is typically done either by dragging a fishing net through quiescent water or by placing a stationary basket trap into a stream. We transfer these general concepts to micron-sized self-motile particles moving in a solvent at low Reynolds number and study their collective trapping behaviour by means of computer simulations of a two-dimensional system of self-propelled rods. A chevron-shaped obstacle is dragged through the active suspension with a constant speed $v$ and acts as a trapping net. Three trapping states can be identified corresponding to no trapping, partial trapping and complete trapping and their relative stability is studied as a function of the apex angle of the wedge, the swimmer density and the drag speed $v$. When the net is dragged along the inner wedge, complete trapping is facilitated and a partially trapped state changes into a complete trapping state if the drag speed exceeds a certain value. Reversing the drag direction leads to a reentrant transition from no trapping, complete trapping, back to no trapping upon increasing the drag speed along the outer wedge contour. The transition to complete trapping is marked by a templated self-assembly of rods forming polar smectic structures anchored onto the inner contour of the wedge. Our predictions can be verified in experiments of artificial or microbial swimmers confined in microfluidic trapping devices.
For many applications, it is important to catch collections of autonomously navigating microbes and man-made microswimmers in a controlled way. Here we propose an efficient trap to collectively capture self-propelled colloidal rods. By means of computer simulation in two dimensions, we show that a static chevron-shaped wall represents an optimal boundary for a trapping device. Its catching efficiency can be tuned by varying the opening angle of the trap. For increasing angles, there is a sequence of three emergent states corresponding to partial, complete, and no trapping. A trapping `phase diagram maps out the trap conditions under which the capture of self-propelled particles at a given density is rendered optimal.
Using extensive Brownian dynamics computer simulations, the long-time self-diffusion coefficient is calculated for Gaussian-core particles as a function of the number density. Both spherical and rod-like particles interacting via Gaussian segments ar$ For increasing concentration we find that the translational self-diffusion behaves non-monotonically reflecting the structural reentrance effect in the equilibrium phase diagram. Both in the limits of zero and infinite concentration, it approaches its short-time value. The microscopic Medina-Noyola theory qualitatively accounts for the translational long-time diffusion. The long-time orientational diffusion coefficient for Gaussian rods, on the other hand, remains very close to its short-time counterpart for any density. Some implications of the weak translation-rotation coupling for ultrasoft rods are discussed.
We consider an off-lattice liquid crystal pair potential in strictly two dimensions. The potential is purely repulsive and short-ranged. Nevertheless, by means of a single parameter in the potential, the system is shown to undergo a first-order phase transition. The transition is studied using mean-field density functional theory, and shown to be of the isotropic-to-nematic kind. In addition, the theory predicts a large density gap between the two coexisting phases. The first-order nature of the transition is confirmed using computer simulation and finite-size scaling. Also presented is an analysis of the interface between the coexisting domains, including estimates of the line tension, as well as an investigation of anchoring effects.
