What is a chemostat? Insights from hybrid dynamics and stochastic thermodynamics
At the microscopic scale, open chemical reaction networks are described by stochastic reactions that follow mass-action kinetics and are coupled to chemostats. We show that closed chemical reaction networks -- with specific stoichiometries imposed by mass-action kinetics -- behave like open ones in the limit where the abundances of a subset of species become macroscopic, thus playing the role of chemostats. We prove that this limit is thermodynamically consistent by recovering the local detailed balance condition of open chemical reaction networks and deriving the proper expression of the entropy production rate. In particular, the entropy production rate features two contributions: one accounting for the dissipation of the stochastic reactions, the other for the dissipation of continuous reactions controlling the chemostats. Finally, we illustrate our results for two prototypical examples.
Code (0)
등록된 구현이 없습니다.
Similar Papers 제목 키워드 기반
A numerical approach to determine mutant invasion fitness and evolutionary singular strategies
We propose a numerical approach to study the invasion fitness of a mutant and to determine evolutionary singular strategies in evolutionary structured models in which the competitive exclusion principle holds. Our approa…
A RBA model for the chemostat modeling
The purpose of this paper is to show that it is possible to replace Monod's type model of a chemostat by a constraint based model of bacteria at the genome scale. This new model is an extension of the RBA model of bacter…
modelThermodynamics of Growth in Open Chemical Reaction Networks
We identify the thermodynamic conditions necessary to observe indefinite growth in homogeneous open chemical reaction networks (CRNs) satisfying mass action kinetics. We also characterize the thermodynamic efficiency of …
A chemostat model with variable dilution rate due to biofilm growth
In many real life applications, a continuous culture bioreactor may cease to function properly due to bioclogging which is typically caused by the microbial overgrowth. This is a problem that has been largely overlooked …
CHyLL: Learning Continuous Neural Representations of Hybrid Systems
Learning the flows of hybrid systems that have both continuous and discrete time dynamics is challenging. The existing method learns the dynamics in each discrete mode, which suffers from the combination of mode switchin…