Inverse modeling of thin layer flow cells for detection of solubility, transport and reaction coefficients from experimental data

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Date
2015
Volume
2161
Issue
Journal
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Publisher
Berlin : Weierstraß-Institut für Angewandte Analysis und Stochastik
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Abstract

Thin layer flow cells are used in electrochemical research as experimental devices which allow to perform investigations of electrocatalytic surface reactions under controlled conditions using reasonably small electrolyte volumes. The paper introduces a general approach to simulate the complete cell using accurate numerical simulation of the coupled flow, transport and reaction processes in a flow cell. The approach is based on a mass conservative coupling of a divergence-free finite element method for fluid flow and a stable finite volume method for mass transport. It allows to perform stable and efficient forward simulations that comply with the physical bounds namely mass conservation and maximum principles for the involved species. In this context, several recent approaches to obtain divergence-free velocities from finite element simulations are discussed. In order to perform parameter identification, the forward simulation method is coupled to standard optimization tools. After an assessment of the inverse modeling approach using known real-istic data, first results of the identification of solubility and transport data for O2 dissolved in organic electrolytes are presented. A plausibility study for a more complex situation with surface reactions concludes the paper and shows possible extensions of the scope of the presented numerical tools.

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Keywords
Stokes equations, mixed finite elements, convection diffusion equation, finite volume method, electrochemical flow cell
Citation
Fuhrmann, J., Linke, A., Merdon, C., Neumann, F., Streckenbach, T., Baltruschat, H., & Khodayari, M. (2015). Inverse modeling of thin layer flow cells for detection of solubility, transport and reaction coefficients from experimental data (Vol. 2161). Berlin : Weierstraß-Institut für Angewandte Analysis und Stochastik.
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