AVS 53rd International Symposium
    Applied Surface Science Monday Sessions
       Session AS-MoA

Invited Paper AS-MoA3
Multivariate Analysis of Correlated Spectral Images

Monday, November 13, 2006, 2:40 pm, Room 2005

Session: Developing Methods for Data Analysis
Presenter: J.A. Ohlhausen, Sandia National Laboratories
Authors: J.A. Ohlhausen, Sandia National Laboratories
M.R. Keenan, Sandia National Laboratories
P.G. Kotula, Sandia National Laboratories
V.S. Smentkowski, General Electric Global Research Center
Correspondent: Click to Email
Spectral imaging is a very powerful approach for collecting large amounts of potentially very useful data needed to characterize a material surface. The challenge arises with analyzing the large data sets in an unbiased way. This challenge can be overcome for single spectral images using multivariate statistical analysis (MSA) methods developed at Sandia. This presentation describes the application of MSA to the even greater challenge of correlated analyses. Specific examples that will be described include: Correlating positive-ion TOF-SIMS spectral images from multiple specimens comparing different process conditions; Correlating TOF-SIMS spectral images in the depth dimension to perform comprehensive 3D analysis; Correlating positive and negative TOF-SIMS spectral images from the same areas of a specimen; Correlating TOF-SIMS and electron-excited x-ray spectral images; and finally the correlation of XPS spectral images with Valence Band spectral images. Remaining challenges and pitfalls in correlated single- and multiple-technique spectral image analyses will also be discussed. Sandia is 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.