Tuning the performance of a micrometer-sized Stirling engine through reservoir engineering

Area of Science:

• Thermodynamics
• Statistical Mechanics
• Nanotechnology

Background:

• Colloidal heat engines model heat-to-work conversion in noisy environments relevant to nano/micro machines.
• Their operation in standard thermal baths is understood, but performance in non-Gaussian, memoryless noise baths is unclear.

Purpose of the Study:

• To quantify the performance of a colloidal Stirling engine operating between a non-Gaussian and a Gaussian bath.
• To investigate the impact of non-Gaussian noise statistics on engine performance and power output.

Main Methods:

• Engineered a memoryless non-Gaussian bath and a standard Gaussian bath.
• Operated a colloidal Stirling engine between these two baths.
• Analyzed engine performance in the quasistatic limit and at increasing operating speeds.

Main Results:

• In the quasistatic limit, the non-Gaussian engine performed similarly to a thermal engine.
• Increasing operating speed caused earlier irreversibility in the non-Gaussian engine compared to the Gaussian one.
• The optimal operating speed for maximum power output was shifted due to non-Gaussian noise.

Conclusions:

• The performance of nano/micro machines, like colloidal heat engines, can be tuned by manipulating reservoir noise statistics.
• Non-Gaussian noise introduces unique behaviors in engine operation, affecting irreversibility and optimal power output speed.