Escape dynamics of active particles in multistable potentials.

Area of Science:

• Non-equilibrium statistical mechanics
• Soft matter physics
• Nanotechnology

Background:

• Rare transitions between metastable states are crucial in diverse physical, chemical, and biological processes.
• Kramers' dynamical framework, based on transition state theory, explains these transitions but fails for systems with non-conservative forces or correlated noise.
• Active particles, which exhibit self-propulsion, represent a significant class of such systems relevant to biology and nanotechnology.

Purpose of the Study:

• To investigate the escape dynamics of active particles from a bistable potential.
• To understand how engineered self-propulsion influences transition rates.
• To explore the existence of an active turnover phenomenon analogous to Kramers turnover.

Main Methods:

• Experimental study of a silica nanoparticle trapped in a bistable potential.
• Introduction of engineered stochastic forces to emulate self-propulsion (activity).
• Theoretical analysis to support experimental findings and elucidate underlying mechanisms.

Main Results:

• Observed that engineered self-propulsion significantly alters escape dynamics.
• Discovered an optimal correlation time for the stochastic force that maximizes the transition rate.
• Identified an "active turnover" behavior, where increasing activity initially enhances, then reduces, the transition rate.

Conclusions:

• The study demonstrates a novel mechanism for controlling transition rates in non-equilibrium systems.
• The findings extend Kramers' theory to active particle systems, revealing an active turnover.
• Establishes a versatile experimental platform for studying single-particle dynamics in active, non-equilibrium environments.