Motional consensus of self-propelled particles.

The motional consensus of self-propelled particles is studied in both noise-free cases and cases with noise by the standard Vicsek model. In the absence of noise, we propose a simple method, using grid-based technique and defining the normalized variance of the ratio of the number of particles locally to globally, to quantitatively study the movement pattern of the system by the spatial distribution of the particles and the degree of aggregation of particles. It is found that the weaker correlation of velocity leads to larger degree of aggregation of the particles. In the cases with noise, we quantify the competition between velocity alignment and noise by considering the difference of the variety of order parameter result from the velocity alignment and noise. The variation of the effect of noise on motional consensus is non-monotonic for the change of the probability distribution of noise from uniform to non-uniform. Our results may be useful and encourage further efforts in exploring the basic principles of collective motion.

Programmable self-propelling actuators enabled by a dynamic helical medium.

Rotation-translation conversion is a popular way to achieve power transmission in machinery, but it is rarely selected by nature. One unique case is that of bacteria swimming, which is based on the collective reorganization and rotation of flagella. Here, we mimic such motion using the light-driven evolution of a self-organized periodic arch pattern. The range and direction of translation are altered by separately varying the alignment period and the stimulating photon energy. Programmable self-propelling actuators are realized via a specific molecular assembly within a photoresponsive cholesteric medium. Through rationally presetting alignments, parallel transports of microspheres in customized trajectories are demonstrated, including convergence, divergence, gathering, and orbital revolution. This work extends the understanding of the rotation-translation conversion performed in an exquisitely self-organized system and may inspire future designs for functional materials and intelligent robotics.