Automated Analysis of X-Ray Spectrum Images from the STEM

Abstract For failure analysis and process control it is critical to perform comprehensive microanalysis. The desire to perform this analysis thoroughly but quickly is the ultimate goal. Typical analyses of this sort have been performed by collecting x-ray spectra at points, along lines, by mapping, and more recently by spectrum imaging where a complete x-ray spectrum is collected over a 2D array of points. Spectrum imaging is perhaps of greatest interest for its potential to thoroughly and comprehensively sample a given area of a microstructure. The problem is that the techniques available for analyzing large (> 1000 spectra) spectrum image (SI) data sets have been limited to mapping after the fact and perhaps thresholding the maps and summing the resultant spectra from those pixels. As a result, there is a need for more sophisticated SI analysis tools, capable of reducing the SI to its essence-the chemical components. Software is currently commercially available for the automated analysis of x-ray spectrum images (SIs) from the SEM