Optimization-based simultaneous modelling of stoichiometries and kinetics in complex organic reaction system

•A novel optimization-based modeling method is proposed for homogeneous organic reaction system.•The proposed modeling method simultaneously addresses stoichiometry identification and kinetics fitting.•Through reformulation from MINLP and MIQP, a final MILP model is developed with high computational...

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Bibliographic Details
Published in:Chemical engineering science 2023-07, Vol.276, p.118758, Article 118758
Main Authors: Xing, Yafeng, Dong, Yachao, Zhou, Wenjin, Du, Jian, Meng, Qingwei
Format: Article
Language:English
Subjects:
Data-driven
Organic reaction
Reaction kinetics
Simultaneous modelling
Stoichiometry
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Summary:•A novel optimization-based modeling method is proposed for homogeneous organic reaction system.•The proposed modeling method simultaneously addresses stoichiometry identification and kinetics fitting.•Through reformulation from MINLP and MIQP, a final MILP model is developed with high computational efficiency.•Two examples are presented to demonstrate the accuracy and effectiveness of the proposed methodology. Efficient understanding and modelling of kinetics in complex organic reaction systems are crucial in the development cycle. The dynamic experimental measurements can be analyzed automatically by the data-driven method in a stepwise modelling approach: after the preliminary screening of candidate stoichiometries, they are formed into different stoichiometric groups, and the reaction data were regressed for each stoichiometric group so that the best fitting kinetic model could be selected. However, the stepwise modelling approach brings about the computational difficulty for complex reaction systems due to the combinatorial nature of forming stoichiometric groups. In this article, a novel optimization-based method, simultaneously combining stoichiometry grouping and kinetics fitting, is proposed to build the kinetic model of a homogeneous organic reaction system. Through reformulation of the original nonlinear optimization model, a mixed integer linear programming model is developed to identify the reaction stoichiometries and kinetic parameters with improved efficiency. Two computational examples are presented to demonstrate the accuracy and effectiveness of the simultaneous modelling methodology.
ISSN:0009-2509
1873-4405
DOI:10.1016/j.ces.2023.118758