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Active nonequilibrium processes are characterized by the coupling of an ionic current or a mechanical motion to a chemical reaction. This coupling induces energy transduction, satisfying Onsager reciprocal relations in the linear regime close to equilibrium and the bivariate fluctuation relation in regimes farther away from equilibrium. These considerations concern, in particular, molecular motors as well as active colloidal particles that are self-propelled by chemical reactions catalyzed at their surface and diffusiophoresis. These active processes can be described by stochastic processes obeying bivariate fluctuation relations for the coupled currents. The mechanochemical coupling can be characterized in terms of the linear and nonlinear response coefficients, as well as the efficiencies defined in the different regimes of energy transduction, i.e., propulsion by the chemical reaction on the one hand, and the synthesis of fuel from products on the other hand.
The experimental observation of driven Brownian motion and an analogous electric circuit confirms that the thermodynamic entropy production can be measured using the probabilities of the paths and their time reversal, i.e., from time asymmetry in temporal disorder. In this way, irreversibility is observed down to the nanometric scale in the position of the driven Brownian particle and a few thousand electron charges in the driven electric circuit. In addition, underdamped and overdamped driven Langevin processes are shown to obey the fluctuation relation and its consequences are discussed. The following examples are considered: a particle moving in a periodic potential and driven by an external force, a driven noisy pendulum, a driven noisy Josephson tunneling junction, the stochastic motion of a charged particle in electric and magnetic fields, and heat transport driven by thermal reservoirs.
At the macroscale, thermodynamics rules the balances of energy and entropy. In nonisolated systems, the entropy changes due to the contributions from the internal entropy production, which is always nonnegative according to the second law, and the exchange of entropy with the environment. The entropy production is equal to zero at equilibrium and positive out of equilibrium. Thermodynamics can be formulated either locally for continuous media or globally for systems in contact with several reservoirs. Accordingly, the entropy production is expressed in terms of either the local or the global affinities and currents, the affinities being the thermodynamic forces driving the system away from equilibrium. Depending on the boundary and initial conditions, the system can undergo relaxation towards equilibrium or nonequilibrium stationary or time-dependent macrostates. As examples, thermodynamics is applied to diffusion, electric circuits, reaction networks, and engines.
Boltzmann’s equation ruling the time evolution of the one-particle distribution function is obtained by partitioning the phase space into the free-flight and collision domains in low-density gases. The expressions for the entropy production and the entropy exchange are related to the H-theorem. The transport properties and gas-surface interactions are discussed. Furthermore, the multivariate fluctuation relation for the energy and particle fluxes is deduced from the fluctuating Boltzmann equation. In addition, an integral fluctuation relation is established for the Boltzmann factorization of the multiparticle probability density into one-particle distribution functions.
The mathematical foundations of transport properties are analyzed in detail in several Hamiltonian dynamical models. Deterministic diffusion is studied in the multibaker map and the Lorentz gases where a point particle moves in a two-dimensional lattice of hard disks or Yukawa potentials. In these chaotic models, the diffusive modes are constructed as the eigenmodes of the Liouvillian dynamics associated with Pollicott–Ruelle resonances. These eigenmodes are distributions with a fractal cumulative function. As a consequence of this fractal character, the entropy production calculated by coarse graining has the expression expected for diffusion in nonequilibrium thermodynamics. Furthermore, Fourier’s law for heat conduction is shown to hold in many-particle billiard models, where heat conductivity can be evaluated with very high accuracy at a conductor-insulator transition. Finally, mechanothermal coupling is illustrated with models for motors propelled by a temperature difference.
Starting from the principles of fluctuating chemohydrodynamics, several nonequilibrium systems are investigated in order to deduce fluctuation relations for particle transport, reactive events, and electric currents with the methods presented in the previous chapters. Moreover, finite-time fluctuation theorems are obtained for stochastic processes with rates linearly depending on the random variables. In this way, fluctuation relations can be established for transport by diffusion, diffusion-influenced surface reactions, ion transport, diodes, transistors, and Brownian motion ruled by the generalized Langevin equation deduced from fluctuating hydrodynamics.
The stroboscopic observation of stochastic processes records the history of the system as paths, which can be characterized by their probability distribution. Temporal disorder results in the exponential decay of the path probabilities as the observational time increases. The mean decay rate defines the so-called entropy per unit time, which measures the amount of temporal disorder in the process. At equilibrium, the probabilities of a path and its time reversal are equal by the principle of detailed balance. In contrast, they differ under nonequilibrium conditions, which is the manifestation of irreversibility. Remarkably, the ratio of the probabilities of opposite paths has a logarithm obeying a fluctuation relation and having a mean value related to the thermodynamic entropy production rate. These results show that temporal ordering can be generated in nonequilibrium processes as a corollary of the second law. These considerations shed new light on Landauer’s principle.
Effusion is one of the most elementary kinetic processes, to which the concepts of nonequilibrium statistical mechanics can be applied. Remarkably, the stationary probability distribution can be exactly constructed as a so-called Poisson suspension, explicitly showing that time reversal is broken at the statistical level of description under nonequilibrium conditions. The multivariate fluctuation relation for the energy and particle currents can be directly deduced from the underlying microscopic dynamics. Moreover, temporal disorder and its nonequilibrium time asymmetry can be fully characterized and shown to be related to the thermodynamic entropy production. The multivariate fluctuation relation can also be applied to mass separation by effusion.
Hydrodynamics is deduced from the microscopic dynamics using local equilibrium probability distributions for multicomponent normal fluids and the phases of matter with broken continuous symmetries such as crystals and liquid crystals. The Nambu–Goldstone modes resulting from continuous symmetry breaking are identified at the microscopic level of description. The entropy and the entropy production are introduced within the local equilibrium approach in agreement with the second law of thermodynamics. The Green–Kubo formulas are obtained for all the transport coefficients associated with the linear response properties, including the cross-coupling effects satisfying the Onsager–Casimir reciprocal relations as a consequence of microreversibility. The boundary conditions due to the presence of interfaces are discussed, as well as the hydrodynamic long-time tails and their consequences, especially, in low-dimensional systems.
This book provides a comprehensive and self-contained overview of recent progress in nonequilibrium statistical mechanics, in particular, the discovery of fluctuation relations and other time-reversal symmetry relations. The significance of these advances is that nonequilibrium statistical physics is no longer restricted to the linear regimes close to equilibrium, but extends to fully nonlinear regimes. These important new results have inspired the development of a unifying framework for describing both the microscopic dynamics of collections of particles, and the macroscopic hydrodynamics and thermodynamics of matter itself. The book discusses the significance of this theoretical framework in relation to a broad range of nonequilibrium processes, from the nanoscale to the macroscale, and is essential reading for researchers and graduate students in statistical physics, theoretical chemistry and biological physics.
Percolation theory is a well studied process utilized by networks theory to understand the resilience of networks under random or targeted attacks. Despite their importance, spatial networks have been less studied under the percolation process compared to the extensively studied non-spatial networks. In this Element, the authors will discuss the developments and challenges in the study of percolation in spatial networks ranging from the classical nearest neighbors lattice structures, through more generalized spatial structures such as networks with a distribution of edge lengths or community structure, and up to spatial networks of networks.