Recent years have seen increased crossover of microscopy techniques developed for transmission electron microscopes (TEMs) being utilized as well in scanning electron microscopes (SEMs). The order of magnitude lower beam energies available in SEMs correspond with significantly different beam-sample interactions that must be accounted for when examining freestanding films. This is especially important for composition analysis via energy dispersive X-ray spectroscopy (EDS) since lower-energy transmission experiments mean X-ray volumes become comparable to sample dimensions. To better understand this scenario, we report results of an SEM-EDS study of terraced freestanding films comprising binary compounds with well-defined atomic ratios. Guided by Monte Carlo simulations, EDS line scan data were collected at different beam energies across segments of varying thicknesses. The results of quantification analysis using different models are compared for multiple combinations of beam energy, sample thickness, and material density, from which some general guidelines are provided for SEM-EDS analysis of freestanding films.

Electron backscatter diffraction (EBSD) is a micro-analytical technique typically attached to a scanning electron microscope (SEM). The vast majority of EBSD measurements is applied to planar and polished surfaces of polycrystalline bulk specimen. In this paper, we present examples of using EBSD and energy-dispersive X-ray spectroscopy (EDX) to analyze specimens that are not flat, not planar, or not bulk – but pillars, needles, and rods. The benefits of low vacuum SEM operation to reduced drift problems are displayed. It is further demonstrated that small and thin specimens enhance the attainable spatial resolution for orientation mapping (by EBSD or transmission Kikuchi diffraction) as well as for element mapping (by EDX).

The degradation of Sydney sandstone used to build the heritage St Mary's Cathedral in Sydney, Australia, has been investigated using environmental scanning electron microscopy combined with energy dispersive X-ray spectroscopy. This technique provided the structural details of the cementing clay and an elemental characterization the sandstone. The observed differences in the elemental composition of the unweathered and weathered sandstones were associated with changes to the clay microstructure upon weathering. The results support the substitution theory that Fe3+ replaces Al3+ in the kaolinite clay component upon weathering. An examination of the impurities present prior to a nonstructural iron removal treatment revealed the presence of minerals that may provide a source of the elements responsible for the substitution process.

Despite the many demonstrated applications of factor analysis (FA) in analyzing hyperspectral materials images, FA does have inherent mathematical limitations, preventing it from solving certain materials characterization problems. A notable limitation of FA is its parsimony restriction, referring to the fact that in FA the number of components cannot exceed the chemical rank of a dataset. Clustering is a promising alternative to FA for the phase classification of hyperspectral materials images. In contrast with FA, the phases extracted by clustering do not have to be parsimonious. Clustering has an added advantage in its insensitivity to spectral collinearity that can result in phase mixing using FA. For representative energy dispersive X-ray spectroscopy materials images, namely a solder bump dataset and a braze interface dataset, clustering generates phase classification results that are superior to those obtained using representative FA-based methods. For the solder bump dataset, clustering identifies a Cu-Sn intermetallic phase that cannot be isolated using FA alone due to the parsimony restriction. For the braze interface sample that has collinearity among the phase spectra, the clustering results do not exhibit the physically unrealistic phase mixing obtained by multivariate curve resolution, a commonly utilized FA algorithm.