IDEAS home Printed from https://ideas.repec.org/a/nat/natcom/v5y2014i1d10.1038_ncomms5721.html
   My bibliography  Save this article

The unlikely Carnot efficiency

Author

Listed:
  • Gatien Verley

    (Complex Systems and Statistical Mechanics, University of Luxembourg)

  • Massimiliano Esposito

    (Complex Systems and Statistical Mechanics, University of Luxembourg)

  • Tim Willaert

    (Theoretical physics, Hasselt University)

  • Christian Van den Broeck

    (Theoretical physics, Hasselt University)

Abstract

The efficiency of an heat engine is traditionally defined as the ratio of its average output work over its average input heat. Its highest possible value was discovered by Carnot in 1824 and is a cornerstone concept in thermodynamics. It led to the discovery of the second law and to the definition of the Kelvin temperature scale. Small-scale engines operate in the presence of highly fluctuating input and output energy fluxes. They are therefore much better characterized by fluctuating efficiencies. In this study, using the fluctuation theorem, we identify universal features of efficiency fluctuations. While the standard thermodynamic efficiency is, as expected, the most likely value, we find that the Carnot efficiency is, surprisingly, the least likely in the long time limit. Furthermore, the probability distribution for the efficiency assumes a universal scaling form when operating close-to-equilibrium. We illustrate our results analytically and numerically on two model systems.

Suggested Citation

  • Gatien Verley & Massimiliano Esposito & Tim Willaert & Christian Van den Broeck, 2014. "The unlikely Carnot efficiency," Nature Communications, Nature, vol. 5(1), pages 1-5, December.
  • Handle: RePEc:nat:natcom:v:5:y:2014:i:1:d:10.1038_ncomms5721
    DOI: 10.1038/ncomms5721
    as

    Download full text from publisher

    File URL: https://www.nature.com/articles/ncomms5721
    File Function: Abstract
    Download Restriction: no

    File URL: https://libkey.io/10.1038/ncomms5721?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Sarmah, Manash Jyoti & Goswami, Himangshu Prabal, 2023. "Learning coherences from nonequilibrium fluctuations in a quantum heat engine," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 627(C).

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:nat:natcom:v:5:y:2014:i:1:d:10.1038_ncomms5721. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.nature.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.