Hostname: page-component-78c5997874-ndw9j Total loading time: 0 Render date: 2024-11-05T06:45:18.371Z Has data issue: false hasContentIssue false
  • English
  • Français

Linking TEM Analytical Spectroscopies for an Assumptionless Compositional Analysis

Published online by Cambridge University Press:  06 March 2014

Gerald Kothleitner ,
Werner Grogger ,
Martina Dienstleder  and
Ferdinand Hofer
Gerald Kothleitner*
Affiliation:
Institute for Electron Microscopy and Nanoanalysis (FELMI), Graz University of Technology and Centre for Electron Microscopy, Steyrergasse 17, 8010 Graz, Austria
Werner Grogger
Affiliation:
Institute for Electron Microscopy and Nanoanalysis (FELMI), Graz University of Technology and Centre for Electron Microscopy, Steyrergasse 17, 8010 Graz, Austria
Martina Dienstleder
Affiliation:
Institute for Electron Microscopy and Nanoanalysis (FELMI), Graz University of Technology and Centre for Electron Microscopy, Steyrergasse 17, 8010 Graz, Austria
Ferdinand Hofer
Affiliation:
Institute for Electron Microscopy and Nanoanalysis (FELMI), Graz University of Technology and Centre for Electron Microscopy, Steyrergasse 17, 8010 Graz, Austria
*
*Corresponding author. [email protected]
Get access

Abstract

The classical implementation for putting quantitative figures on maps to reveal elemental compositions in transmission electron microscopy is by analytical methods like X-ray and energy-loss spectroscopy. Typically, the technique in use often depends on whether lighter or heavier elements are present and—more practically—which calibrations are available or sample-related properties are known. A framework linking electron energy-loss spectroscopy (EELS) and energy-dispersive X-ray (EDX) signals such that absolute volumetric concentrations can be derived without assumptions made a priori about the unknown sample, is largely missing. In order to combine both techniques and harness their respective potentials for a light and heavy element analysis, we have set up a powerful hardware configuration and implemented an experimental approach, which reduces the need for estimates on many parameters needed for quantitative work such as densities, absolute thicknesses, theoretical ionization cross-sections, etc. Calibrations on specimens with known geometry allow the measurement of inelastic mean free paths. As a consequence, mass-thicknesses obtained from the EDX ζ-factor approach can be broken up and quantities like concentrations and partial energy-differential ionization cross-sections become accessible. ζ-factors can then be used for conversion into EELS cross-sections that are hard to determine otherwise, or conversely, connecting EDXS and EELS in a quantitative manner quite effectively.

Keywords

X-ray analysisEELS analysiselemental quantificationζ-factorsabsorptionEELS cross-sectionschemical shifts
Type
EDGE Special Issue
Information
Microscopy and Microanalysis , Volume 20 , Issue 3 , June 2014 , pp. 678 - 686
Copyright
© Microscopy Society of America 2014 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Auchterlonie, G.J., McKenzie, D.R. & Cockayne, D.J.H. (1989). Using ELNES with parallel EELS for differentiating between a-Si: X thin films. Ultramicroscopy 31(2), 217–221.CrossRefGoogle Scholar
Cliff, G. & Lorimer, G.W. (1975). The quantitative analysis of thin specimens. J Microsc 103, 203–207.CrossRefGoogle Scholar
Craven, A.J., Wilson, J.A. & Nicholson, W.A.P. (2002). A fast beam switch for controlling the intensity in electron energy loss spectrometry. Ultramicroscopy 92, 165–180.CrossRefGoogle ScholarPubMed
Hunt, J.A. & Williams, D.B. (1991). Electron energy-loss spectrum-imaging. Ultramicroscopy 38(1), 47–73.CrossRefGoogle Scholar
Egerton, R.F. (2011). Electron Energy-Loss Spectroscopy in the Electron Microscope. New York, Dordrecht, Heidelberg, and London: Springer.CrossRefGoogle Scholar
Freitag, B., Knippels, G., Kujawa, S., Tiemeijer, P.C., Van der Stam, M., Hubert, D., Kisielowski, C., Denes, P., Minor, A. & Dahmen, U. (2008). First performance measurements and application results of a new high brightness Schottky emitter for HR-S/TEM at 80–300 kV acceleration voltage. In EMC 2008 Instrumentation and Methods 1, Luysberg, M., Tillman, K. & Weirich, T. (Eds.), pp. 55–56. Berlin Heidelberg, Germany: Springer Verlag.Google Scholar
Goldstein, J.I., Williams, D.B. & Cliff, G. (1986). Quantification of energy dispersive spectra. In Quantification of Energy Dispersive Spectra in Principles of Analytical Electron Microscopy, Joy, D.C., Romig, A.D. & Goldstein, J.I. (Eds.), pp. 155–217. New York: Plenum Press.CrossRefGoogle Scholar
Gubbens, A., Barfels, M., Trevor, C., Twesten, R., Mooney, P., Thomas, P., Menon, N., Kraus, B., Mao, C. & McGinn, B. (2010). The GIF Quantum, a next generation post-column imaging energy filter. Ultramicroscopy 110(8), 962–970.CrossRefGoogle Scholar
Heinrich, K.F.J. (1987). Mass absorption coefficients for electron probe microanalysis. In Proceedings of the 11 th International Congress on X-ray Optics and Microanalysis, University of Western Ontario , Brown, J.D. & Packwood, R.H. (Eds.), pp. 67–377. London, Ontario: University of Western Ontario.Google Scholar
Hofer, F. & Wilhelm, P. (1993). EELS microanalysis of the elements Ca to Cu using M23 edges. Ultramicroscopy 49(1–4), 189–197.CrossRefGoogle Scholar
Jeanguillaume, C. & Colliex, C. (1989). Spectrum-image: The next step in EELS digital acquisition and processing. Ultramicroscopy 28, 252–257.CrossRefGoogle Scholar
Kimoto, K., Sekiguchi, T. & Aoyama, T. (1997). Chemical shift mapping of Si L and K edges using spatially resolved EELS and energy-filtering TEM. J Electron Microsc 46(5), 369–374.CrossRefGoogle Scholar
Kothleitner, G. & Hofer, F. (2003). Elemental occurrence maps: A starting point for quantitative EELS spectrum image processing. Ultramicroscopy 96, 491–508.CrossRefGoogle ScholarPubMed
Kothleitner, G., Neish, M.J., Lugg, N.R., Findlay, S.D., Grogger, W., Hofer, F. & Allen, L.J. (2014). Quantitative Elemental Mapping at Atomic Resolution Using X-Ray Spectroscopy. Phys Rev Lett 112, 0855011–0855015.CrossRefGoogle Scholar
Longo, P. & Twesten, R. (2013). Fast STEM spectrum imaging using simultaneous EELS and EDS. Microsc Today 21(1), 28–33.CrossRefGoogle Scholar
Malis, T., Cheng, S.C. & Egerton, R.F. (1988). EELS log-ratio technique for specimen-thickness measurment in the TEM. J Electron Microsc Tech 8, 193–200.CrossRefGoogle ScholarPubMed
Pauling, L. (1960). The Nature of the Chemical Bond. US: Cornell University Press.Google Scholar
Pinna, H. & Tencé, M. (2006). CNRS. Device for obtaining the image and/or spectra of electron energy loss. US Patent FR2874124A1.Google Scholar
Schlossmacher, P., Klenov, D.O., Freitag, B. & von Harrach, H.S. (2010). Enhanced detection sensitivity with a new windowless XEDS system for AEM based on silicon drift detector technology. Microsc Today 18, 14–20.CrossRefGoogle Scholar
Scott, J., Thomas, P.J., MacKenzie, M., McFadzean, S., Wilbrink, J., Craven, A.J. & Nicholson, W.A.P. (2008). Near-simultaneous dual energy range EELS spectrum imaging. Ultramicroscopy 108(12), 1586–1594.CrossRefGoogle ScholarPubMed
Terborg, R. & Rohde, M. (2004). Properties and applications of new silicon drift detectors and multiple element silicon drift detectors. Microsc Microanal 10(Suppl 2), 942–943.CrossRefGoogle Scholar
Watanabe, M. & Williams, D.B. (2006). The quantitative analysis of thin specimens: A review of progress from the Cliff–Lorimer to the new ζ-factor methods. J Microsc 221, 89–109.CrossRefGoogle Scholar
Xin, H.L. Dwyer, C. & Muller, D.A. (2014). Is there a Stobbs factor in atomic-resolution STEM-EELS mapping? Ultramicroscopy 139, 38–46.CrossRefGoogle Scholar