Optimal run-and-tumble based transportation of a Janus particle with active steering
arXiv:1610.01485 · doi:10.1073/pnas.1616013114
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 α. 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 α. 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.
References in corpus (5)
- Self-motile colloidal particles: from directed propulsion to random walk
- Propulsion of a molecular machine by asymmetric distribution of reaction--products
- Induced-charge Electrophoresis of Metallo-dielectric Particles
- Capped colloids as light-mills in optical traps
- Validity of Fluctuation Theorem on Self-Propelling Particles
Cited by in corpus (35)
- Tuning the random walk of active colloids
- A Geometric Criterion for the Optimal Spreading of Active Polymers in Porous Media
- Optimal steering of a smart active particle
- Clustering and flocking of repulsive chiral active particles with non-reciprocal couplings
- Clustering and phase separation of circle swimmers dispersed in a monolayer
- Dynamical Clustering Interrupts Motility Induced Phase Separation in Chiral Active Brownian Particles
- Autophoretic motion in three dimensions
- Learning to Control Active Matter
- Analytical approach to chiral active systems: suppressed phase separation of interacting Brownian circle swimmers
- Active Brownian and inertial particles in disordered environments: short-time expansion of the mean-square displacement
- Quorum-sensing active particles with discontinuous motility
- Spin glasses : experimental signatures and salient outcomes
- Microscopic theory for hyperuniformity in two-dimensional chiral active fluid
- Emergence of colloidal patterns in AC electrical fields
- Hot Particles Attract in a Cold Bath
- Pair correlation of dilute Active Brownian Particles: from low activity dipolar correction to high activity algebraic depletion wings
- Optimal navigation of microswimmers in complex and noisy environments
- Active particles in non-inertial frames: how to self-propel on a carousel
- Efficient control protocols for an active Ornstein-Uhlenbeck particle
- Optimal navigation strategies for microswimmers on curved manifolds
- Long-range translational order and hyperuniformity in two-dimensional chiral active crystal
- Microscopic thermal machines using run-and-tumble particles
- Active Transport of Cargo-Carrying and Interconnected Chiral Particles
- Singular density correlations in chiral active fluids in three dimensions
- Optimal switching strategies for navigation in stochastic settings
- Inverted Sedimentation of Active Particles in Unbiased ac Fields
- Chirality, confinement and dimensionality govern re-entrant transitions in active matter
- Hierarchical deep reinforcement learning controlled three-dimensional navigation of microrobots in blood vessels
- A Deep Reinforcement Learning Architecture for Multi-stage Optimal Control
- Algebraic correlations and anomalous fluctuations in ordered flocks of Janus particles fueled by an AC electric field
- Active chiral molecules in activity gradients
- Effective diffusion of a tracer in active bath: a path-integral approach
- Mobile Microelectrodes: Towards active spatio-temporal control of the electric field and selective cargo assembly
- Micro/Nano Motor Navigation and Localization via Deep Reinforcement Learning
- Riding the Wave: Polymers in Time-dependent Nonequilibrium Baths