Hostname: page-component-cd9895bd7-8ctnn Total loading time: 0 Render date: 2024-12-28T04:14:06.303Z Has data issue: false hasContentIssue false
  • English
  • Français

Misidentification of Major Constituents by Automatic Qualitative Energy Dispersive X-ray Microanalysis: A Problem that Threatens the Credibility of the Analytical Community

Published online by Cambridge University Press:  15 November 2005

Dale E. Newbury*
Dale E. Newbury*
Affiliation:
Surface and Microanalysis Science Division, National Institute of Standards and Technology, Gaithersburg, MD 20899-8370, USA
Get access

Abstract

Automatic qualitative analysis for peak identification is a standard feature of virtually all modern computer-aided analysis software for energy dispersive X-ray spectrometry with electron excitation. Testing of recently installed systems from four different manufacturers has revealed the occasional occurrence of misidentification of peaks of major constituents whose concentrations exceeded 0.1 mass fraction (10 wt%). Test materials where peak identification failures were observed included ZnS, KBr, FeS2, tantalum-niobium alloy, NIST Standard Reference Material 482 (copper–gold alloy), Bi2Te3, uranium–rhodium alloys, platinum–chromium alloy, GaAs, and GaP. These misidentifications of major constituents were exacerbated when the incident beam energy was 10 keV or lower, which restricted or excluded the excitation of the high photon energy K- and L-shell X-rays where multiple peaks, for example, Kα (K-L2,3)–Kβ (K-M2,3); Lα (L3-M4,5)–Lβ (L2-M4)–Lγ (L2-N4), are well resolved and amenable to identification with high confidence. These misidentifications are so severe as to properly qualify as blunders that present a serious challenge to the credibility of this critical analytical technique. Systematic testing of a peak identification system with a suite of diverse materials can reveal the specific elements and X-ray peaks where failures are likely to occur.

Keywords

analytical electron microscopyautomated analysisenergy dispersive X-ray spectrometrypeak identificationqualitative analysisscanning electron microscopytransmission electron microscopyX-ray microanalysis
Type
Microanalysis
Information
Microscopy and Microanalysis , Volume 11 , Issue 6 , December 2005 , pp. 545 - 561
Copyright
© 2005 Microscopy Society of America

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

REFERENCES

Bevington, P.R. & Robinson, D.K. (1992). Data Reduction and Error Analysis for the Physical Sciences, 2nd ed. New York: McGraw-Hill.
Fiori, C.E. & Newbury, D.E. (1978). Artifacts observed in energy dispersive X-ray spectrometry in the scanning electron microscope. Scan Electron Microsc 1, 401–422.Google Scholar
Fiori, C., Swyt, C., & Myklebust, R. (1991). Desktop Spectrum Analyzer (DTSA), a Comprehensive Software Engine for Electron-Excited X-ray Spectrometry. National Institute of Standards and Technology, Standard Reference Data Program, Gaithersburg, MD. Available at: thttp://www.cstl.nist.gov/div837/Division/outputs/software.htm.
Goldstein, J., Newbury, D., Joy, D., Lyman, C., Echlin, P., Lifshin, E., Sawyer, L., & Michael, J. (2003). Scanning Electron Microscopy and X-ray Microanalysis, 3rd ed., pp. 355–390. New York: Kluwer Academic Plenum Press.CrossRef
Taylor, J. (1997). An Introduction to Error Analysis, 2nd ed. Sausalito, CA: University Science Books.
Williams, D.B. & Carter, C.B. (1996). Transmission Electron Microscopy, pp. 587–598. New York: Plenum.CrossRef