Quantitative surface microanalysis of samples with extreme topography utilising image interpretation by scatter diagrams and principal component analysis

Quantitative surface analysis (by Auger imaging, SIMS, EPMA, etc.) of many samples of technological interest is not possible due to the image artefacts arising from surface topography or other features of the sample. A methodology is presented for the identification and removal of regions within an image where artefacts dominate the contrast. This enables meaningful quantification of the regions not dominated by artefacts. The method employs multi-variate statistical techniques including 3D scatter diagrams and principal component analysis (PCA). PCA proves to be a powerful method for measuring the extent of any remnant artefact within image sets. The methodology is applied to the characterisation of a PtRh catalyst using the multi-spectral scanning Auger microscope at York.