Optimal run-and-tumble based transportation of a Janus particle with active steering

TL;DR

This paper introduces a feedback-based run-and-tumble guidance method for synthetic Janus particles, enabling robust and optimized navigation in noisy environments through deterministic steering controlled by electric field modulation.

Contribution

It presents a novel active steering technique for Janus particles using electric fields, combining numerical, analytical, and experimental validation of an optimized feedback algorithm.

Findings

The steering method is robust against particle variability.

Optimal tolerance angle improves targeting accuracy.

Experimental validation confirms simulation predictions.

Abstract

Even though making artificial micrometric swimmers has been made possible by using various propulsion mechanisms, guiding their motion in the presence of thermal fluctuations still remains a great challenge. Such a task is essential in biological systems, which present a number of intriguing solutions that are robust against noisy environmental conditions as well as variability in individual genetic makeup. Using synthetic Janus particles driven by an electric field, we present a feedback-based particle guiding method, quite analogous to the "run-and-tumbling" behavior of Escherichia coli but with a deterministic steering in the tumbling phase: the particle is set to the "run" state when its orientation vector aligns with the target, while the transition to the "steering" state is triggered when it exceeds a tolerance angle {\alpha}. The active and deterministic reorientation of the particle is achieved by a characteristic rotational motion that can be switched on and off by modulating the AC frequency of the electric field, first reported in this work. Relying on numerical simulations and analytical results, we show that this feedback algorithm can be optimized by tuning the tolerance angle {\alpha}. The optimal resetting angle depends on signal to noise ratio in the steering state, and it is demonstrated in the experiment. Proposed method is simple and robust for targeting, despite variability in self-propelling speeds and angular velocities of individual particles.