Anomalous Dynamics of Superparamagnetic Colloidal Microrobots with Tailored Statistics

TL;DR

This paper demonstrates superparamagnetic colloidal microrobots with customizable stochastic dynamics, capable of mimicking biological anomalous diffusion patterns like Lévy walks and fractional Brownian motion, across large spatial and temporal scales.

Contribution

It introduces a method to fully control the anomalous diffusion behavior of microrobots by tuning their step-length and velocity autocorrelation, enabling biomimetic stochastic navigation.

Findings

Achieved control over the entire spectrum of anomalous diffusion in microrobots.

Successfully mimicked biological movement patterns such as Lévy walks and fractional Brownian motion.

Demonstrated potential for programmable navigation in medical and environmental applications.

Abstract

Living organisms have developed advanced motion strategies for efficient space exploration, serving as inspiration for the movements of microrobots. These real-life strategies often involve anomalous dynamics displaying random movement patterns that deviate from Brownian motion. Despite their biological inspiration, autonomous stochastic navigation strategies of current microrobots remain much less versatile than those of their living counterparts. Supported by theoretical reasoning, this work demonstrates superparamagnetic colloidal microrobots with fully customizable stochastic dynamics displaying the entire spectrum of anomalous diffusion, from subdiffusion to superdiffusion, across statistically significant spatial and temporal scales (covering at least two decades). By simultaneously tuning microrobots' step-length distribution and, critically, their velocity autocorrelation function with magnetic fields, fundamental anomalous dynamics are reproduced with tailored properties mimicking L\'evy walks and fractional Brownian motion. These findings pave the way for programmable microrobotic systems that replicate optimal stochastic navigation strategies found in nature for applications in medical robotics and environmental remediation.