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FlowMat: a toolbox for modeling flow reactors using physics-based and machine learning approaches for modular simulation; parameter identification; and reactor optimization
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DOI：10.1039/D5RA06173C.png)
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Abstract
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This paper introduces a versatile; open-source MATLAB/Simulink toolbox for modeling and optimizing flow reactors. The toolbox features a modular architecture and an intuitive drag-and-drop interface; supporting a range of different modeling approaches; including physics-based; data-driven; and hybrid models such as physics-informed neural networks. We detail the toolbox's implementation and demonstrate its capabilities through real-world applications; including the simulation of flow reactors; identification of reaction parameters using experimental data (e.g.; transient data); and optimization of reactor operating points and configurations. Experimental validations illustrate the practical applicability and effectiveness of the toolbox; making it a valuable resource for researchers and engineers in the field with the potential of reducing the cost and time required for parameter determination and reactor optimization.
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