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Area of Science:

  • Mesoscopic Thermodynamics
  • Stochastic Thermodynamics
  • Brownian Motion

Background:

  • Traditional heat engines utilize macroscopic working substances like gases and liquids.
  • Recent advancements enable the study and design of single-particle heat engines.
  • These systems require analysis within the framework of stochastic thermodynamics.

Purpose of the Study:

  • To design and analyze a mesoscopic heat engine utilizing a Brownian particle.
  • To investigate the performance of a Stirling-like heat engine operating in the irreversible, non-quasi-static regime.
  • To optimize the thermodynamic cycle for maximum output power.

Main Methods:

  • A Brownian particle confined in a harmonic trap and immersed in a thermal bath.
  • Design of a Stirling-like cycle with isothermal and isochoric branches.
  • Application of variational calculus and optimal control theory to determine optimal driving protocols.

Main Results:

  • The study focuses on finite-duration cycles, enabling non-zero output power.
  • Optimal driving protocols were derived to maximize delivered power.
  • Numerical exploration of the dependence of maximum output power and efficiency on system parameters.

Conclusions:

  • Mesoscopic heat engines with Brownian particles can be designed and optimized.
  • Optimal control theory provides a powerful tool for maximizing power output in non-quasi-static thermodynamic cycles.
  • Understanding these systems is crucial for advancing practical applications of micro- and nanoscale energy conversion.