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Entropy 2017, 19(7), 356;

Clausius Relation for Active Particles: What Can We Learn from Fluctuations

CNR-ISC and Dipartimento di Fisica, Sapienza Università di Roma, p.le A. Moro 2, 00185 Roma, Italy
Scuola di Scienze e Tecnologie, Università di Camerino, Via Madonna delle Carceri, 62032 Camerino, Italy
Istituto Nazionale di Fisica Nucleare (INFN), Perugia 06123, Italy
Author to whom correspondence should be addressed.
Received: 12 June 2017 / Revised: 6 July 2017 / Accepted: 12 July 2017 / Published: 13 July 2017
(This article belongs to the Special Issue Thermodynamics and Statistical Mechanics of Small Systems)
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Many kinds of active particles, such as bacteria or active colloids, move in a thermostatted fluid by means of self-propulsion. Energy injected by such a non-equilibrium force is eventually dissipated as heat in the thermostat. Since thermal fluctuations are much faster and weaker than self-propulsion forces, they are often neglected, blurring the identification of dissipated heat in theoretical models. For the same reason, some freedom—or arbitrariness—appears when defining entropy production. Recently three different recipes to define heat and entropy production have been proposed for the same model where the role of self-propulsion is played by a Gaussian coloured noise. Here we compare and discuss the relation between such proposals and their physical meaning. One of these proposals takes into account the heat exchanged with a non-equilibrium active bath: such an “active heat” satisfies the original Clausius relation and can be experimentally verified. View Full-Text
Keywords: active particles; entropy production; Clausius relation active particles; entropy production; Clausius relation
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).

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Puglisi, A.; Marini Bettolo Marconi, U. Clausius Relation for Active Particles: What Can We Learn from Fluctuations. Entropy 2017, 19, 356.

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