Tomographic spectral imaging: Data acquisition and analysis via multivariate statistical analysis

Tomographic spectral imaging is a powerful technique for the three-dimensional (3-D) analysis of materials. Using a focused ion-beam/scanning electron microscope equipped with an x-ray spectrometer, 3-D microanalysis can be performed on individual regions of a sample, such as defects, with microanalytical spatial resolution of better than 300 nm typically. The focused ion-beam can serially section at comparable thicknesses to sequentially reveal new analytical surfaces within the specimen. After each slice a full 2-spatial dimension spectral image, consisting of a complete spectrum at each point in the 2-D array, is acquired with the scanning electron microscope/energy-dispersive x-ray spectrometer on the same platform. The process is repeated multiple times to result in a 3-D or tomographic spectral image. The challenge is to effectively and efficiently analyze the tomographic spectral image to extract chemical phase distributions. Therefore, automated multivariate statistical analysis methods were developed and applied to these images. Sandia’s Automated eXpert Spectral Image Analysis multivariate statistical analysis software requires no a priori information to find even very weak signals hidden in the data sets. The result of the analysis is a small number of chemical components which describe the 3-D phase distribution in the volume of material sampled. These 3-D phases can then be effectively visualized with off-the-shelf 3-D rendering software.