A comparison of PCA and MAF for ToF-SIMS image interpretation

While 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 (C) 2009 John Wiley & Sons, Ltd.