The application of spectroscopic processing techniques to multi-spectral XPS data sets has enabled the acquisition of quantitative surface chemical state images. Such data sets are necessarily large, incorporating many spectra, so prohibiting interactive processing. Instead multivariate analytical techniques are used to reduce the dimensionality of the data, and also to increase the signal/noise, there bye speeding acquisition. These techniques may also be used to classify regions in images according to different chemistry, that is changes in photoelectron intensity, changes in binding energy and changes in the inelastic background. Spectra from classified regions may then be summed to aid visualisation, obviating the need for multivariate curve resolution with its attendant uncertainties. Further the inelastic background of transmission corrected spectra from classified regions may be modelled to provide spatially resolved in-depth information. Such classification also aids curve fitting, since curve fit models can be applied to regions of similar chemistry.
IntroductionX-ray photoelectron spectroscopy is a mature surface analytical technique, with a large installed instrument base, providing relatively easily quantified chemical state information, which is reflected by the number of publications in scientific journals. However, despite the fact that the first commercially available XPS instrument capable of imaging was announced in 1990, [1] relatively few publications, by comparison, have concerned imaging XPS. This is a consequence of instrument manufacturers implementing the acquisition of single energy images as a guide to selected area analysis, and as a result, losing the very features that made XPS spectroscopy popular, namely, quantification and the acquisition of chemical state information. Single energy images, and even peak minus background images, are incapable of accounting for the background below photoelectron peaks, or for changes in the peak shape due to chemical shifts. Further, they cannot resolve overlapping photoelectron peaks. Indeed, even as a guide to selected area analysis, single energy images perform poorly, since they can only truly represent changes occurring across an image if there are only two components which change. Yet the acquisition of quantifiable chemical state images is clearly preferable to analyses at a number of discrete points.More recently, however, a number of publications have described the acquisition of spectrum image datasets, [2] where each pixel in an image contains a spectrum. Such datasets may be acquired by scanning an X-ray probe over the surface while acquiring a spectrum at each pixel, or by acquiring a series of energy-filtered images incremented in energy, known as parallel imaging. The latter mode is preferred since it is quicker and minimises sample damage due to X-ray exposure. Two different types of instruments are capable of parallel acquisition. One employs a cathode lens, [3] the other a combination magnetic/electrostatic lens. Using laborator...