AVS 51st International Symposium
    Applied Surface Science Wednesday Sessions
       Session AS-WeM

Paper AS-WeM3
Identifying Surface Chemical Changes with XPS Spectral Imaging and Multivariate Statistical Analysis@footnote 1@

Wednesday, November 17, 2004, 9:00 am, Room 210A

Session: Chemometric Analysis of Spectral or Image Data; XPS/TOF-SIMS Applications
Presenter: D.E. Peebles, Sandia National Laboratories
Authors: D.E. Peebles, Sandia National Laboratories
J.A. Ohlhausen, Sandia National Laboratories
K.R. Zavadil, Sandia National Laboratories
M.R. Keenan, Sandia National Laboratories
P.G. Kotula, Sandia National Laboratories
Correspondent: Click to Email
Imaging X-ray Photoelectron Spectroscopy (XPS) allows the distribution of elements and chemical states to be mapped across a surface region of interest. Conventional use of XPS mapping involves utilizing images acquired at peak intensities for chemical species of interest with the subtraction of a suitable background image off the peak. Both peak and background image energies need to be determined from a prior spectrum taken from the imaged region to insure optimal energy selection. While this allows differentiation of chemical states, image contrast and resolution may be poor, especially for overlapping spectral peaks. A more complete and definitive picture of the distribution of chemical species across the surface may be obtained by acquiring a series of images over an energy range that covers the peaks of interest. This generates a very large amount of data that must be processed and correlated, generally with some form of multivariate statistical analysis. Many types of multivariate statistical analyses require user input for the number of species present and their general lineshape. Others produce non-physical spectra that may be difficult to interpret. Multivariate statistical analysis methods developed at Sandia National Laboratories facilitate the rapid analysis of the large quantities of data produced by spectral imaging in an efficient manner without user bias or input. The use of these methods for XPS spectral images to detect changes in chemical state will be demonstrated. In particular, examples illustrating the ability of these techniques to resolve overlapping peaks and reveal correlated species will be included. @FootnoteText@ @footnote 1@ This work was completed at Sandia National Laboratories, a multiprogram laboratory operated by Sandia Corporation, a Lockheed Martin Company, for the United States Department of Energy's National Nuclear Security Administration under contract DE-AC04-94AL85000.