Framework Of Stochastic Thermodynamics Research Articles

Energy versus information based estimations of dissipation using a pair of magnetic colloidal particles.

Using the framework of stochastic thermodynamics, we present an experimental study of a doublet of magnetic colloidal particles that is manipulated by a time-dependent magnetic field. Because of hydrodynamic interactions, each bead experiences a state-dependent friction, which we characterize using a hydrodynamic model. In this work, we compare two estimates of the dissipation in this system: the first one is energy based since it relies on the measured interaction potential, while the second one is information based since it uses only the information content of the trajectories. While the latter only offers a lower bound of the former, we find it to be simple to implement and of general applicability to more complex systems.

Optimal stochastic transport in inhomogeneous thermal environments

We consider the optimization of the average entropy production in inhomogeneous temperature environments within the framework of stochastic thermodynamics. For systems modeled by Langevin equations (e.g. a colloidal particle in a heat bath) it has been recently shown that a space-dependent temperature breaks the time reversal symmetry of the fast velocity degrees of freedom resulting in an anomalous contribution to the entropy production of the overdamped dynamics. We show that optimization of entropy production is determined by an auxiliary deterministic problem formally analogous to motion on a curved manifold in a potential. The “anomalous contribution” to entropy plays the role of the potential and the inverse of the diffusion tensor is the metric. We also find that entropy production is not minimized by adiabatically slow, quasi-static protocols but there is a finite optimal duration for the transport process. As an example we discuss the case of a linearly space-dependent diffusion coefficient.

Fact-Checking Ziegler’s Maximum Entropy Production Principle beyond the Linear Regime and towards Steady States

We challenge claims that the principle of maximum entropy production produces physical phenomenological relations between conjugate currents and forces, even beyond the linear regime, and that currents in networks arrange themselves to maximize entropy production as the system approaches the steady state. In particular: (1) we show that Ziegler’s principle of thermodynamic orthogonality leads to stringent reciprocal relations for higher order response coefficients, and in the framework of stochastic thermodynamics, we exhibit a simple explicit model that does not satisfy them; (2) on a network, enforcing Kirchhoff’s current law, we show that maximization of the entropy production prescribes reciprocal relations between coarse-grained observables, but is not responsible for the onset of the steady state, which is, rather, due to the minimum entropy production principle.

Stochastic dynamics, efficiency and sustainable power production

In the framework of stochastic thermodynamics, we give a precise expression of power dissipation in a heat engine, and study the relation between entropy and power dissipation. Using these relations, we propose a reasonable and general definition of efficiency for thermal engines in a non-equilibrium stationary state. This definition, different from Carnot efficiency, seems appropriate to the concerns of sustainable development. We show that non-zero dissipation is necessary for producing non-vanishing power. Furthermore, close to equilibrium and even in much broader situations, when power production is maximum with respect to relevant variables the power dissipation is at less equal to the power delivered to a mechanical, external system, and the corresponding “sustainable efficiency” is at most ½. From this result, we deduce a new upper bound for Carnot efficiency at maximum power. It is compared to similar, but different upper bounds obtained previously by other authors.