Abstract
AbstractWhile time‐of‐flight secondary ion mass spectrometry (ToF‐SIMS) image generation has been useful in the determination of the spatial distribution of chemistry in a broad application area, the amount of secondary ion signal available in each pixel remains small, hampering the use of multivariate analysis (MVA) approaches. The pre‐treatment of data commonly comprises two approaches to increase pixel signal intensity prior to MVA: mass channel summation and pixel summation. Recent advances in instrumentation have lead to much greater signal per image pixel such that a true spectrum can be discerned at each point across the sample. In this study, we determine the outcomes of these two pre‐treatments prior to principal components analysis (PCA) and maximum autocorrelation factor (MAF) analysis in comparison with high signal intensity data.Both PCA and MAF analyses of the high signal intensity data are presented with MAF being identified as the most effective approach. Image data was reduced in intensity to determine the effectiveness of MVA with lower spectral intensity. MAF was found to outperform PCA on such data, although both techniques were useful in the identification of the chemistry present. The data were then mass summed, using a number of different approaches, to reduce mass resolution, leading to a detrimental effect on PCA analysis, but little discernable change to MAF output. Reducing the spatial resolution by summing spectra from adjacent pixels, however, lead to a severe blurring of the MAF image structure, with PCA performing well.Conclusions and recommendation for pre‐treatment and MVA technique selection are presented. Copyright © 2009 John Wiley & Sons, Ltd.
Highlights
When generating SIMS images with ToF-SIMS instruments equipped with pulsed primary sources of atomic ions there is a limit to the amount of molecular information than can be generated from each pixel.[1]
We examined four mass binning strategies to determine their influence on the outcome of Principal components analysis (PCA) and Maximum autocorrelation factor analysis (MAF) analyses: 1 u, 0.5 u and 0.1 u all centred on nominal mass and 0.5 u with the bin edge aligned to nominal mass
The five most intense positively loaded spectral features for both PCA and MAF were selected for use in a fingerprint library search.[25]
Summary
When generating SIMS images with ToF-SIMS instruments equipped with pulsed primary sources of atomic ions there is a limit to the amount of molecular information than can be generated from each pixel.[1]. The approach of Keenan and Kotula, commonly called Poisson scaling, attempts to account for this by performing a scaling such that the estimated variance due to counting statistics is equal on all variables (intensity values at different masses) so multivariate analysis can better account for other sources of variance, for example those due to sample chemistry.
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