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The thermodynamic processes can be classified into reversible and irreversible processes. The processes that can be restored to their initial state are called reversible processes. It is only possible if the process is in quasi-static equilibrium, i.e., it takes place in infinitesimally small steps, and the system remains at equilibrium However, these are ideal processes and do not occur naturally. An ideal system undergoing a reversible process is always in thermodynamic equilibrium within...
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Stochastic approach to irreversible thermodynamics.

Grégoire Nicolis1, Yannick De Decker1

  • 1Center for Nonlinear Phenomena and Complex Systems (CENOLI), Université libre de Bruxelles (ULB), Campus Plaine, C.P. 231, B-1050 Brussels, Belgium.

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Summary

This study extends irreversible thermodynamics by incorporating microscopic fluctuations into macroscopic observables. This new framework quantifies fluctuation contributions to entropy production in reactive systems.

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Area of Science:

  • Thermodynamics
  • Statistical Mechanics
  • Chemical Kinetics

Background:

  • Classical irreversible thermodynamics, pioneered by Ilya Prigogine, provides a foundation for understanding non-equilibrium systems.
  • Macroscopic descriptions often neglect fluctuations arising from underlying microscopic processes.
  • Understanding these fluctuations is crucial for a complete picture of system dynamics.

Purpose of the Study:

  • To develop an extended framework of irreversible thermodynamics that explicitly incorporates fluctuations.
  • To derive a method for quantifying the contribution of these fluctuations to entropy production.
  • To analyze the impact of fluctuations in reactive systems, considering both linear and nonlinear dynamics.

Main Methods:

  • Extension of classical irreversible thermodynamics.
  • Development of a generalized entropy balance equation.
  • Application of an extended local equilibrium Ansatz to relate macroscopic and microscopic variables.
  • Analysis of probability distributions of fluctuating variables.

Main Results:

  • A method to derive the contribution of fluctuations to entropy production.
  • The contribution is expressed in terms of fluctuating variables and their probability distributions.
  • The approach is demonstrated on reactive systems with linear and nonlinear steps.

Conclusions:

  • The developed framework provides a more comprehensive understanding of irreversible processes by including fluctuations.
  • The study highlights the importance of fluctuations, especially in systems far from equilibrium and those with nonlinear dynamics.
  • This extension offers new avenues for analyzing complex chemical and physical systems.