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Universality of Efficiency at Maximum Power
Open accessAbstract
We investigate the efficiency of power generation by thermochemical engines. For strong coupling between the particle and heat flows and in the presence of a left-right symmetry in the system, we demonstrate that the efficiency at maximum power displays universality up to quadratic order in the deviation from equilibrium. A maser model is presented to illustrate our argument.
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Cites
Network theory of microscopic and macroscopic behavior of master equation systems
Schnakenberg, J. (1976) · Reviews of Modern Physics · doi:10.1103/revmodphys.48.571 · Cited by 1,122
Cited by
Stochastic thermodynamics, fluctuation theorems and molecular machines
Seifert, U. (2012) · Reports on Progress in Physics · doi:10.1088/0034-4885/75/12/126001 · Cited by 3,300
Fundamental aspects of steady-state conversion of heat to work at the nanoscale
Benenti, G., Casati, G., Saito, K., & Whitney, R. S. (2017) · Physics Reports · doi:10.1016/j.physrep.2017.05.008 · Cited by 664
Equivalence of Quantum Heat Machines, and Quantum-Thermodynamic Signatures
Uzdin, R., Levy, A., & Kosloff, R. (2015) · Physical Review X · doi:10.1103/physrevx.5.031044 · Cited by 412
Stochastic thermodynamics under coarse graining
Esposito, M. (2012) · Physical Review E · doi:10.1103/physreve.85.041125 · Cited by 398
Self-citationEnsemble and trajectory thermodynamics: A brief introduction
Van den Broeck, C., & Esposito, M. (2015) · Physica A: Statistical Mechanics and its Applications · doi:10.1016/j.physa.2014.04.035 · Cited by 365
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Metadata
- Authors
- Esposito, M., Lindenberg, K., & Van den Broeck, C.
- Venue
- Physical Review Letters
- Publisher
- American Physical Society (APS)
- Published
- 2009-04-01
- Volume
- 102
- Issue
- 13
- Pages
- 130602-130602
- ISSN
- 0031-9007 (ISSN-L)
- 1079-7114
- OpenAlex
- W2004562907
- Cited by
- 415
- References
- 1
- FWCI
- 17.83
- Type
- journal article
- Language
- en
- Open access
- green
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.