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Parameter identification in cyclic voltammetry of alkaline methanol oxidation

 
: Clees, T.; Nikitin, I.; Nikitina, L.; Pott, S.; Krewer, U.; Haisch, T.

:

Rango, F. de:
8th International Conference on Simulation and Modeling Methodologies, Technologies and Applications, SIMULTECH 2018. Proceedings : July 29-31, 2018, Porto, Portugal
SciTePress, 2018
ISBN: 978-989-758-323-0
S.279-288
International Conference on Simulation and Modeling Methodologies, Technologies and Applications (SIMULTECH) <8, 2018, Porto>
Englisch
Konferenzbeitrag
Fraunhofer SCAI ()
complex systems modeling and simulation; non-linear optimization; parameter identification; application in electrochemistry

Abstract
Alkaline methanol oxidation is an electrochemical process, perspective for the design of efficient high energy density fuel cells. The process involves a large number of elementary reactions, forming a complex reaction graph, and it is described by a system of non-linear differential equations of high order. The purpose of parameter identification is a reconstruction of reaction constants in this model on the basis of available experimental data. Cyclic voltammetry, a measurement of dynamical current-voltage characteristic of the cell, is especially suitable for analysis of electrochemical kinetics. In this paper we present several approaches for parameter identification in cyclic voltammetry of alkaline methanol oxidation. With the aid of global optimization methods and interactive parameter study we find four islands of solutions in parameter space, corresponding to different chemical mechanisms of the process. The main features of solutions are discussed and the reconstructed reaction constants are presented.

: http://publica.fraunhofer.de/dokumente/N-524016.html