Experimentally observable transitions between dynamical states in complex reaction systems

Abstract

Identification of trends and their correspondence with dynamical state transitions are briefly discussed on several reaction network models. The influence of different threshold values on the trend analysis and dynamical state analysis results is examined. Both methods are applied here to the results of the numerical simulation. For this purpose the models of three reaction systems are used: simple model of consecutive, first order, equilibrium reactions, partial oxidation of cyclohexane, and model of the oscillatory reaction Bray Liebhafsky. Detailed kinetic analysis confirmed that transient dynamical states may be identified through the symbolic representation of the sequence of trend episodes in experimentally obtainable time series. Stoichiometric Network Analysis of possible dynamical states was used to identify reaction pathways responsible for the sequences of trend episodes. Some technical problems were also addressed, connected with selection of the threshold value and dynamical state notion.