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Statistical and Principal Component Analysis in the Design of Alkaline Methanol Fuel Cells

Authors:
Tanja Clees
Bernhard Klaassen
Igor Nikitin
Lialia Nikitina
Sabine Pott

Keywords: modeling of complex systems; observational data and simulations; advanced applications; mathematical chemistry.

Abstract:
In this paper, the electrochemical alkaline methanol oxidation process, which is relevant for the design of efficient fuel cells, is considered. An algorithm for reconstructing the reaction constants for this process from the experimentally measured polarization curve is presented. The approach combines statistical and principal component analysis and determination of the trust region for a linearized model. It is shown that this experiment does not allow one to determine accurately the reaction constants, but only some of their linear combinations. The possibilities of extending the method to additional experiments, including dynamic cyclic voltammetry and variations in the concentration of the main reagents, are discussed.

Pages: 1 to 5

Copyright: Copyright (c) IARIA, 2021

Publication date: October 3, 2021

Published in: conference

ISSN: 2308-4499

ISBN: 978-1-61208-887-7

Location: Barcelona, Spain

Dates: from October 3, 2021 to October 7, 2021