AVS 53rd International Symposium
    Surface Science Thursday Sessions
       Session SS-ThP

Paper SS-ThP17
Multivariate Analysis as an Enabling Method for Structure-to-Property Studies of Fuel Cell Electrocatalysts

Thursday, November 16, 2006, 5:30 pm, Room 3rd Floor Lobby

Session: Surface Science Poster Session
Presenter: S. Pylypenko, The University of New Mexico
Authors: S. Pylypenko, The University of New Mexico
T.S. Olson, The University of New Mexico
M. Dowlapalli, The University of New Mexico
K. Artyushkova, The University of New Mexico
J.E. Fulghum, The University of New Mexico
P. Atanassov, The University of New Mexico
Correspondent: Click to Email
Understanding the surface chemistry and structure of electrocatalysts, and linking structure to properties is important for optimization of catalyst performanace and elucidation of failure mechanisms. Characterization of the changes in surface chemistry that occur as a function of catalyst production, modification and aging requires identification of subtle changes in a complex system. X-ray photoelectron spectroscopy (XPS) in combination with multivariate analysis (MVA) was used to study a number of materials, including non-platinum electrocatalysts, based on pyrolysed porphyrins, and carbon blacks used as catalyst supports. Analysis of chemical bonding information from XPS spectra frequently utilizes deconvolution of the spectra into multiple peaks, resulting in significant interpretational ambiguities. Multivariate analysis techniques, in combination with conventional curve fitting, facilitate both interpretation of the data and the development of structure-property correlations. Principal component analysis (PCA) was applied to the XPS curve fit results from the catalysts and supports, enabling identification of chemical species, grouping of chemical species as a function of catalyst treatment, and correlation with electrochemical performance. The methodology applied in this study can be effectively used to identify active catalytic sites responsible for oxidation/reduction process, detect chemical species responsible for corrosion of the catalyst material, and assist in design of optimized electrocatalysts.