2011
DOI: 10.1038/nphys2163
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Realization of a micrometre-sized stochastic heat engine

Abstract: The conversion of energy into mechanical work is essential for almost any industrial process. The original description of classical heat engines by Sadi Carnot in 1824 has largely shaped our understanding of work and heat exchange during macroscopic thermodynamic processes 1 . Equipped with our present-day ability to design and control mechanical devices at micro-and nanometre length scales, we are now in a position to explore the limitations of classical thermodynamics, arising on scales for which thermal flu… Show more

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Cited by 533 publications
(650 citation statements)
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References 25 publications
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“…They coincided with an unprecedented development in the experimental techniques used to manipulate small systems and triggered a great deal of experimental studies in a variety of contexts, such as single molecule stretching experiments [35,[38][39][40], nanomechanical oscillator work measurements [41], spectroscopic measurement of trajectory entropies [42,43], and electronic current fluctuations in full counting statistics experiments [44]. Since stochastic thermodynamics combines kinetics and thermodynamics, it has also proved extremely useful to describe the finite-time thermodynamics (e.g., efficiency at finite power) of various nanodevices operating as thermodynamic machines [45][46][47][48][49][50][51][52][53][54]. Overall, this theory is becoming a fundamental tool for the study of nanosciences.…”
Section: Introductionmentioning
confidence: 99%
“…They coincided with an unprecedented development in the experimental techniques used to manipulate small systems and triggered a great deal of experimental studies in a variety of contexts, such as single molecule stretching experiments [35,[38][39][40], nanomechanical oscillator work measurements [41], spectroscopic measurement of trajectory entropies [42,43], and electronic current fluctuations in full counting statistics experiments [44]. Since stochastic thermodynamics combines kinetics and thermodynamics, it has also proved extremely useful to describe the finite-time thermodynamics (e.g., efficiency at finite power) of various nanodevices operating as thermodynamic machines [45][46][47][48][49][50][51][52][53][54]. Overall, this theory is becoming a fundamental tool for the study of nanosciences.…”
Section: Introductionmentioning
confidence: 99%
“…This model consists of an overdamped Brownian particle confined to one spatial dimension, in a time dependent harmonic potential V (x, t) = Λ(t) 2 x 2 , coupled to a heat bath with a time dependent inverse temperature β(t). This model was suggested in [16] and experimentally realized in [22]. Both Λ(t) and β(t) are periodic with a cycle time τ 1 .…”
mentioning
confidence: 87%
“…On the other hand, driving the engine faster increases the power at the expense of efficiency, until eventually, at fast enough driving, the dissipation rate becomes significant and causes a decrease in power. Yet, as we demonstrate, this behavior is not universal, and there is no inherent trade-off between power and efficiency as a function of the cycle time, although such a trade-off always exists in cycles that exactly attain the Carnot bound.Here we analyze a class of cyclic heat engine models, referred to as geometric heat engines, which includes the paradigmatic examples of a Brownian particle in a parabolic potential [12,13,16,22] and the two-state Markovian engines [23], but is not limited to these models. In this class, the work and heat can be interpreted as areas in state space (the space of all the possible states of the engine) defined by the periodic trajectory of the engine's state.…”
mentioning
confidence: 99%
“…This is the reverse of the protocol that has been studied in [38] in context of single particle stochastic heat engine. There are other important protocols, for example Stirling-type protocol used in earlier studies [19], where the adiabatic steps are absent. The comparative study between stochastic thermodynamics of micro machines driven by different protocols will be focused elsewhere.…”
Section: The Modelmentioning
confidence: 99%