Brownian Carnot engine

• Published in: Nature physics Vol. 12; no. 1; pp. 67 - 70
• Main Authors: Martínez, I. A., Roldán, É., Dinis, L., Petrov, D., Parrondo, J. M. R., Rica, R. A.
• Format: Journal Article
• Language: English
• Published: London Nature Publishing Group UK 01.01.2016; Nature Publishing Group
• Subjects: 639/766/530/2804; 639/766/530/951; Atomic; Classical and Continuum Physics; Complex Systems; Condensed Matter Physics; Design engineering; Energy transfer; Engines; Entropy; Fluctuation; Fluctuations; letter; Mathematical and Computational Physics; Molecular; Motors; Optical and Plasma Physics; Physics; Strategy; Theoretical; Transducers
• ISSN: 1745-2473; 1745-2481
• DOI: 10.1038/nphys3518

Despite the simplicity of the Carnot cycle, realizing it at the microscale is complicated by the difficulty in implementing adiabatic processes. A clever solution subjects a charged particle to a noisy electrostatic force that mimics a thermal bath. The Carnot cycle imposes a fundamental upper limit to the efficiency of a macroscopic motor operating between two thermal baths 1 . However, this bound needs to be reinterpreted at microscopic scales, where molecular bio-motors 2 and some artificial micro-engines 3 , 4 , 5 operate. As described by stochastic thermodynamics 6 , 7 , energy transfers in microscopic systems are random and thermal fluctuations induce transient decreases of entropy, allowing for possible violations of the Carnot limit 8 . Here we report an experimental realization of a Carnot engine with a single optically trapped Brownian particle as the working substance. We present an exhaustive study of the energetics of the engine and analyse the fluctuations of the finite-time efficiency, showing that the Carnot bound can be surpassed for a small number of non-equilibrium cycles. As its macroscopic counterpart, the energetics of our Carnot device exhibits basic properties that one would expect to observe in any microscopic energy transducer operating with baths at different temperatures 9 , 10 , 11 . Our results characterize the sources of irreversibility in the engine and the statistical properties of the efficiency—an insight that could inspire new strategies in the design of efficient nano-motors.