Extraction of useful work from the chaotic environments remains a captivating challenge. A gear in the bath of self-propelling eccentric particles is investigated by computer simulation. We find that the asymmetrical gear can rotate in a specific direction, with the angular speed first increasing and then decreasing as the eccentricity increases. Besides, a machine-learning model is trained to predict the angular speeds and the optimal one. Additionally, we observe that the directional rotation of a symmetric gear depends on the particle-area fraction, the persistence length of motion, and the eccentricity. Eccentricity is not conducive to the rotation of a symmetric gear, but a small degree of eccentricity can help increase the angular speed of the gear. There exist two mechanisms working for gear rotation at low eccentricity of particles: edge alignment with corner trapping and biased trapping with positive feedback. These insights suggest the tunable particle-level parameter, eccentricity, offers a promising strategy to regulate and optimize gear rotation.

Close

PrevNext

View figure in article

• Active Brownian particles
• Dry active matter