Szilard Engines and Information-Based Work Extraction for Active Systems.

Area of Science:

• Statistical Mechanics
• Active Matter Physics
• Thermodynamics

Background:

• Active systems, being out of equilibrium, offer unique opportunities for designing information-based engines.
• The conventional Szilard engine operates in thermal equilibrium and is constrained by the Landauer principle.

Purpose of the Study:

• To design and analyze two types of active Szilard engines that extract work from an active bath.
• To investigate how active Brownian particles can be utilized to overcome the Landauer limit.
• To identify optimal operating conditions for maximizing work extraction and efficiency.

Main Methods:

• Designing two active Szilard engine models utilizing Maxwell demons.
• Employing active baths of noninteracting active Brownian particles.
• Analyzing work extraction by exploiting active pressure and velocity correlation times.

Main Results:

• Both active Szilard engines successfully extract larger amounts of work compared to conventional engines.
• The active bath enables overcoming the Landauer principle's limitations.
• Optimal regimes for maximizing work output and efficiency were identified for both engine designs.

Conclusions:

• Active systems provide a viable pathway for enhanced information-based engines.
• Active Szilard engines offer a route to surpass classical thermodynamic limits.
• The findings have implications for both synthetic and biological active systems.