title: Multivariate statistical analysis of three-spatial-dimension TOF-SIMS raw data sets.
abstract: Three-spatial-dimension (3D) time-of-flight-secondary ion mass spectrometry (TOF-SIMS) analysis can be performed if an X-Y image is saved at each depth of a depth profile. In this paper, we will show how images reconstructed from specified depths, depth profiles generated from specific X-Y coordinates, as well as three-spatial-dimensional rendering provide for a better understanding of the sample than traditional depth profiling where only a single spectrum is collected at each depth. We will also demonstrate, for the first time, that multivariate statistical analysis (MVSA) tools can be used to perform a rapid, unbiased analysis of the entire 3D data set. In the example shown here, retrospective analysis and MVSA revealed a more complete picture of the 3D chemical distribution of the sample than did the as-measured depth profiling alone. Color overlays of the MVSA components as well as animated movies allowing for visualization (in 3D) from various angles will be provided.
authors.affiliation: General Electric, Global Research, Niskayuna, New York 12309, USA. smentkow@research.ge.com
authors.forename: V S
authors.initials: VS
authors.lastname: Smentkowski
authors.forename: S G
authors.initials: SG
authors.lastname: Ostrowski
authors.forename: E
authors.initials: E
authors.lastname: Braunstein
authors.forename: M R
authors.initials: MR
authors.lastname: Keenan
authors.forename: J A
authors.initials: JA
authors.lastname: Ohlhausen
authors.forename: P G
authors.initials: PG
authors.lastname: Kotula