Information Engine Fueled by First-Passage Times

Area of Science:

• Thermodynamics
• Statistical Mechanics
• Nanotechnology

Background:

• Information engines harness thermal fluctuations for work.
• Feedback control is crucial for engine operation.
• First-passage-time distributions characterize system dynamics.

Purpose of the Study:

• Investigate thermodynamic properties of an information engine.
• Derive and experimentally verify fluctuation theorems for information engines.
• Establish bounds on work extraction from thermal fluctuations.

Main Methods:

• Utilized a mechanical cantilever with electrostatic feedback control.
• Employed rapid sampling and threshold-based feedback triggering.
• Calculated information (ΔI) from first-passage-time distributions.

Main Results:

• Derived and experimentally verified two fluctuation theorems involving information (ΔI).
• Established a tight bound on the work produced by the information engine.
• Demonstrated a general framework applicable beyond the specific experimental setup.

Conclusions:

• The study provides a robust framework for fluctuation theorems and work bounds.
• Results are generalizable, relying on probability distributions of protocols.
• Advances understanding of information-to-work conversion in thermodynamic systems.