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Achievable Information-Energy Exchange in a Brownian Information Engine through Potential Profiling.

Rafna Rafeek1, Debasish Mondal1

  • 1Department of Chemistry and Center for Molecular and Optical Sciences and Technologies, Indian Institute of Technology Tirupati, Yerpedu 517619, Andhra Pradesh, India.

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Summary
This summary is machine-generated.

This study explores how potential shaping impacts Brownian information engines (BIEs) that extract work from heat. Concave potentials enhance energy harvesting, and multistable potentials yield greater energy than monostable ones.

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Area of Science:

  • Thermodynamics
  • Statistical Mechanics
  • Information Theory

Background:

  • Information engines extract work from heat using mutual information.
  • Brownian information engines (BIEs) harness thermal fluctuations via feedback cycles.
  • Potential shaping is crucial for optimizing BIE performance.

Purpose of the Study:

  • Investigate the effect of potential shaping on BIEs.
  • Analyze how confinement influences information-energy exchange.
  • Explore BIE performance in monostable, bistable, and multistable potentials.

Main Methods:

  • Designed a BIE with an overdamped Brownian particle in a confined potential.
  • Implemented a symmetric feedback cycle for operation.
  • Analyzed work extraction based on potential shape (convex, concave, bistable, multistable).

Main Results:

  • Monostable confinement efficiency depends on temperature and convexity; concave is better than convex.
  • Bistable confinement shows an engine-to-refrigeration transition beyond a critical barrier height.
  • Multistable potentials, utilizing concavity-induced gain, harvest more energy than monostable ones.

Conclusions:

  • Potential shaping significantly impacts BIE work extraction efficiency.
  • Concave potentials and multistable configurations offer enhanced energy harvesting.
  • BIEs can be optimized through careful design of confining potentials for greater energy gains.