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Asymptotic Thermodynamics for Chemical Reaction Networks with Fast-Slow Kinetics
1School of Computer and Big Data, Minjiang University, Fuzhou 350108, China.
Entropy (Basel, Switzerland)
|July 28, 2026
Summary
This study introduces asymptotic expansions for nonequilibrium thermodynamics in chemical reaction networks (CRNs). The method rigorously analyzes energy and entropy balances in complex, multiscale systems.
Area of Science:
- Chemical kinetics
- Thermodynamics
- Mathematical modeling
Background:
- Chemical reaction networks (CRNs) often exhibit complex kinetics with multiple timescales.
- Understanding nonequilibrium thermodynamics is crucial for analyzing these systems.
- Existing methods may struggle with the multiscale nature of CRNs.
Purpose of the Study:
- To systematically derive asymptotic expansions for nonequilibrium thermodynamics in CRNs.
- To apply singular perturbation theory to analyze fast-slow kinetics.
- To develop a rigorous framework for energy and entropy balance in multiscale CRNs.
Main Methods:
- Systematic derivation of asymptotic expansions using singular perturbation theory.
- Obtaining first and second laws of thermodynamics for the asymptotic expansion model.
- Deriving composite expansions for enthalpy, entropy, entropy production rate, and relative entropy.
- Analyzing convergence orders based on local Lipschitz properties.
Main Results:
- Composite expansions capture long-time trends (outer parts) and fast dynamics (inner parts).
- Enthalpy shows convergence similar to kinetic variables.
- Entropy, relative entropy, and entropy production rate exhibit reduced convergence orders due to logarithmic terms near zero concentrations.
- Validated on the reversible Michaelis-Menten reaction, yielding analytical expansions.
- Numerical simulations confirm accuracy and reveal higher-order convergence for entropy production rate.
Conclusions:
- Composite expansion is a rigorous tool for analyzing energy and entropy balances in multiscale CRNs.
- The method provides physically consistent approximations.
- Understanding convergence properties is key for accurate thermodynamic analysis.
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