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Fluctuation theorem for nonequilibrium reactions.

Pierre Gaspard1

  • 1Center for Nonlinear Phenomena and Complex Systems, Université Libre de Bruxelles, Code Postal 231, Campus Plaine, B-1050 Brussels, Belgium. gaspard@ulb.ac.be

The Journal of Chemical Physics
|July 23, 2004
PubMed
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A new fluctuation theorem for chemical reactions is presented, linking detailed balance loss to entropy production. This finding is verified using the Schlögl model, advancing nonequilibrium thermodynamics.

Area of Science:

  • * Chemical kinetics and thermodynamics
  • * Statistical mechanics and nonequilibrium systems

Background:

  • * Stochastic processes are fundamental to understanding chemical reactions, especially far from equilibrium.
  • * The chemical master equation (CME) describes the probabilistic evolution of chemical systems.
  • * Detailed balance is a key concept in equilibrium thermodynamics, often violated in nonequilibrium conditions.

Purpose of the Study:

  • * To derive a fluctuation theorem for stochastic nonequilibrium reactions governed by the CME.
  • * To characterize fluctuations related to the loss of detailed balance.
  • * To establish and discuss the connection between this theorem and entropy production.

Main Methods:

  • * Derivation of a fluctuation theorem using generating functions and large-deviation theory.

Related Experiment Videos

  • * Application of the theorem to the Schlögl model, a well-known bistable system.
  • * Analysis of the quantity measuring the deviation from thermodynamic equilibrium.

    • Main Results:

    • * A novel fluctuation theorem is established for stochastic chemical reactions.
    • * The theorem quantifies fluctuations associated with the loss of detailed balance.
    • * A direct relationship between the fluctuation theorem and entropy production is demonstrated.

    Conclusions:

    • * The derived fluctuation theorem provides a new tool for analyzing nonequilibrium chemical systems.
    • * The study confirms the theorem's validity in a relevant far-from-equilibrium model.
    • * This work deepens the understanding of thermodynamic principles in stochastic processes.