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在周期性驱动下从相互作用的布朗粒子中获得高效热机。

Obtaining efficient thermal engines from interacting Brownian particles under time-periodic drivings.

作者信息

Mamede Iago N, Harunari Pedro E, Akasaki Bruno A N, Proesmans Karel, Fiore C E

机构信息

Instituto de Física da Universidade de São Paulo, 05314-970 São Paulo, Brazil.

Complex Systems and Statistical Mechanics, Physics and Materials Science Research Unit, University of Luxembourg, L-1511 Luxembourg, Luxembourg.

出版信息

Phys Rev E. 2022 Feb;105(2-1):024106. doi: 10.1103/PhysRevE.105.024106.

Abstract

We introduce an alternative route for obtaining reliable cyclic engines, based on two interacting Brownian particles under time-periodic drivings which can be used as a work-to-work converter or a heat engine. Exact expressions for the thermodynamic fluxes, such as power and heat, are obtained using the framework of stochastic thermodynamic. We then use these exact expression to optimize the driving protocols with respect to output forces, their phase difference. For the work-to-work engine, they are solely expressed in terms of Onsager coefficients and their derivatives, whereas nonlinear effects start to play a role since the particles are at different temperatures. Our results suggest that stronger coupling generally leads to better performance, but careful design is needed to optimize the external forces.

摘要

我们基于两个在周期性驱动下相互作用的布朗粒子,引入了一种获得可靠循环发动机的替代途径,该发动机可用作功 - 功转换器或热机。利用随机热力学框架获得了诸如功率和热量等热力学通量的精确表达式。然后,我们使用这些精确表达式,针对输出力及其相位差来优化驱动协议。对于功 - 功发动机,它们仅根据昂萨格系数及其导数来表示,而由于粒子处于不同温度,非线性效应开始起作用。我们的结果表明,更强的耦合通常会带来更好的性能,但需要精心设计以优化外力。

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