Paper AS-WeM12
A Comparison of Multivariate Statistical Analysis Protocols for ToF-SIMS Spectral Images

Wednesday, October 22, 2008, 11:40 am, Room 207

Time of Flight Secondary Ion Mass Spectrometry (ToF-SIMS) instruments produce raw data sets with a tremendous quantity of data. Multivariate Statistical Analysis (MVSA) tools are being used to boil the massive amount of chemical information into a smaller set of components which are easier to interpret and understand due to species association. Standard Principal Component analysis (PCA) is the most heavily used MVSA algorithm used in the ToF-SIMS community. Other algorithms such as Multivariate Curve Resolution (MCR) have also gained popularity over the past few years. In this work, we compare the as-measured ToF-SIMS spectrum and ion images with four MVSA data analysis protocols; standard PCA, image-rotated PCA, spectra-rotated PCA, and MCR. Image-rotated PCA and spectra-rotated PCA are variations of standard PCA that involve abstract rotation of the principal components, and are designed to enhance either spatial contrast or spectral contrast in the components, respectively. We will show that the four MVSA protocols provide essentially the same information, but accentuate different aspects of the sample’s composition and lateral distribution, and that taken together these methods provide a more complete understanding of the sample. We will demonstrate that the component spectra provided by MVSA protocols assists the analyst in understanding species correlation which would have been difficult, if not impossible, using univariate analysis protocols. Since each component image is represented by an associated spectrum (and not just a single peak) enhanced signal-to-noise and contrast is obtained. For the data set described here, MVSA tools identified unexpected species, which were not obvious in the as measured data.