Gatan Microscopy Suite (GMS) 3.4 Analysis Tools: Model-based EELS quantification and ELNES phase mapping
Please join this webinar to explore the powerful new elemental quantification features available in GMS 3.4.
Built on the existing model-based EELS quantification framework, ELNES phase mapping allows pre-acquired reference spectra (or standards) to be used for quantification in addition to the existing set of calculated cross-section models. Not only does this significantly improve the accuracy of the final quantification results by providing truer edge shapes that can be fitted over large energy ranges, but ELNES phase mapping also enables the separation and quantification of different material phases by allowing multiple reference spectra for the same ionization edge to be imported and used concurrently. This webinar will provide a detailed overview of this new feature drawing on application examples highlighting the new data processing capabilities.
Liam Spillane, Ph.D.
Analytical Applications Specialist, Gatan
Model-Based EELS Quantification and ELNES Phase Mapping Using Experimentally Measured Cross-Sections
Electron-energy-loss spectroscopy (EELS) can reveal a wealth of information about the sample with high sensitivity and high spatial resolution. However, extracting this information in an optimal manner is often non-trivial for a variety of reasons. In recent years, model-based quantification has both simplified and improved the accuracy of the quantification process in EELS (e.g., [1, 2]). It could be shown that using a combination of a power-law decaying background along with theoretically computed cross-sections as a first-order approximation of the expected edge shape gives a reasonably robust way of performing compositional quantification, automatically separating out contributions of overlapping edge shapes in many commonly encountered situations. Provided a suitable EELS low-loss spectrum is available, plural scattering effects can also be incorporated into such an analysis to further improve the quantification. While this approach can greatly improve the reproducibility and accuracy of quantification and allows for very fast map computations in the spectrum-imaging application, some groups of tightly overlapping edges can still not be sufficiently separated automatically. This inability is caused by the theoretical cross-sections not correctly reproducing the electron loss near-edge fine-structure (ELNES) features that are present in experimentally measured spectra.
An improved quantification scheme has been implemented in Gatan Microscopy Suite (GMS) version 3.4.0 that utilizes experimentally measured cross-sections to improve the situation . The cross-section shape is readily derived from background-subtracted spectra, ideally corrected for plural scattering effects, to create an edge ‘standard’. This edge standard can often (and ideally) be obtained directly from the spectrum-image data to be analyzed itself. Scaling of the standard is then either achieved by normalization with theoretically computed cross-sections, or it can be derived from the a-priori knowledge of the sample composition and thickness.
This new approach combines the advantages of the multiple linear least-square (MLLS) fitting of static reference spectra with the model-based quantification scheme. MLLS fitting of pre-measured standards has been shown previously to yield superior quantification compared to conventional background subtraction . It can also achieve clean separation of edges for complex overlapping scenarios and incorporates plural scattering correction at the same time, yielding more accurate maps for specimens with thickness variations across the data. This is achieved in a simple, unified workflow. Furthermore, by allowing multiple concurrent experimental cross-section references to be specified for each individual core-loss edge, ELNES finger-printing can be incorporated into the same quantification routine. This allows the separation of elements of different chemical states to be performed routinely, with plural scattering correction applied, as part of the regular elemental mapping process. This approach will be described, along with practical examples of common application use cases.
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 P.J. Thomas, et al., Microsc. Microanal. 18 (Suppl 2), 2012, p968.
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