Depinning and activated motion of chiral self-propelled particles

We study experimentally, numerically, and analytically, the dynamics of a chiral active particle (cm-sized robots), pulled at a constant translational velocity. We show that these robots can faithfully be described by an overdamped chiral Active Brownian Particle model with self-alignment. We find that the competition between the robots' internal chiral activity and the imposed drive triggers a depinning transition in the noiseless limit, giving rise to a creep regime in the presence of rotational diffusion. The dynamics of the robots can be mapped into a Brownian particle driven across a periodic potential landscape, allowing for an analytical treatment. The steady-state distribution, from which one can construct a dynamic phase diagram, can be computed exactly from the model, across all the dynamical regimes. The active fluctuations introduced by the robots themselves are responsible for an intermittent activated dynamics that allows them to escape their otherwise pinned orientations in a typical time that we derive. Our work thus consolidates such self-propelled robots as an analytically tractable experimental model system for the study of chiral active matter, and highlights the interesting dynamics arising from the interplay between external and internal driving forces in the form of chiral torques, that have been so far avoided in experiments of active particles at granular scales.

Authors

Institutions

Publication Details

Journal
Physical review. E
Published
2025-11-14
DOI
https://doi.org/10.1103/7zmp-z893
Citations
2
Primary Topic
Micro and Nano Robotics
Type
article
Field-Weighted Citation Impact
2.52
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Depinning and activated motion of chiral self-propelled particles

Demian Levis, Juan Pablo Carrillo-Mora, Adrià Garcés
2 citations
Physical review. E
Micro and Nano Robotics
2.52
article

Depinning and activated motion of chiral self-propelled particles

Demian Levis, Juan Pablo Carrillo-Mora, Adrià Garcés
article en
2 citations

Abstract

We study experimentally, numerically, and analytically, the dynamics of a chiral active particle (cm-sized robots), pulled at a constant translational velocity. We show that these robots can faithfully be described by an overdamped chiral Active Brownian Particle model with self-alignment. We find that the competition between the robots' internal chiral activity and the imposed drive triggers a depinning transition in the noiseless limit, giving rise to a creep regime in the presence of rotational diffusion. The dynamics of the robots can be mapped into a Brownian particle driven across a periodic potential landscape, allowing for an analytical treatment. The steady-state distribution, from which one can construct a dynamic phase diagram, can be computed exactly from the model, across all the dynamical regimes. The active fluctuations introduced by the robots themselves are responsible for an intermittent activated dynamics that allows them to escape their otherwise pinned orientations in a typical time that we derive. Our work thus consolidates such self-propelled robots as an analytically tractable experimental model system for the study of chiral active matter, and highlights the interesting dynamics arising from the interplay between external and internal driving forces in the form of chiral torques, that have been so far avoided in experiments of active particles at granular scales.

Physical review. EVol. 112(6)
Universitat de Barcelona (ES)
Openalex Percentile: Top 9%
Micro and Nano Robotics
2.52
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.