Hostname: page-component-586b7cd67f-tf8b9 Total loading time: 0 Render date: 2024-11-22T19:56:09.465Z Has data issue: false hasContentIssue false

35 Years of EDS Software

Published online by Cambridge University Press:  12 November 2009

Frederick H. Schamber*
Affiliation:
Aspex Corporation, 175 Sheffield Drive, Delmont, PA 15626, USA
*
Corresponding author. E-mail: [email protected]
Get access

Abstract

The computerized multichannel analyzer running software specifically designed for X-ray analysis appeared very early in the commercialization of the energy dispersive X-ray spectrometer (EDS) and, like the solid-state X-ray detector itself, was built on a technology foundation originally developed for nuclear spectroscopy. However, software techniques employed for gamma-ray spectra could not accommodate the continuum component of EDS spectra, and a new approach was required. Least-squares fitting with “top-hat” filtered spectra proved to be an effective solution that is still widely used today. Though modern computer technology has subsequently contributed greatly to the speed and convenience of present-day EDS software, it seems that the achievable accuracy and precision of spectrum analysis has not fundamentally improved, and most of the early challenges are still quite relevant, although they may appear in new guises. The availability of the high speed silicon drift detector, however, may provide both the incentive and the data precision to drive future advances. This article traces the formative years of EDS software from the personalized perspective of a participant. Factors that shaped the development of the industry are identified, and future directions are speculated.

Type
Special Section: 40 Years of EDS
Copyright
Copyright © Microscopy Society of America 2009

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. (1969). Data Reduction and Error Analysis for the Physical Sciences. New York: McGraw-Hill.Google Scholar
Fitzgerald, R., Keil, K. & Heinrich, K.F.J. (1968). Solid-state energy-dispersion spectrometer for electron-microprobe X-ray analysis. Science 159(3814), 528530.CrossRefGoogle ScholarPubMed
Goldstein, J.I., Newbury, D.E., Echlin, P., Joy, D.C., Romig, A.D. Jr., Lyman, C.E., Lifshin, E., Sawyer, L. & Michael, J.R. (2003). Scanning Electron Microscopy and X-Ray Microanalysis, 3rd Ed.New York: Springer.CrossRefGoogle Scholar
McCarthy, J., Friel, J. & Camus, P. (2009). Impact of 40 years of technology advances on EDS system performance. Microsc Microanal 15, 484490 (this issue).CrossRefGoogle ScholarPubMed
McCarthy, J.J. (1980). Analysis of X-ray spectra by filtered least-squares fitting. Scanning Electron Microscopy II, 259270.Google Scholar
McCarthy, J.J. & Schamber, F.H. (1979). Least-squares fit with digital filter: A status report. In NBS Special Publication 604: Energy Dispersive X-Ray Spectrometry, Heinrich, K.F.J, Newbury, D.E., Myklebust, R.L. & Fiori, C.E. (Eds.), pp. 273296. Gaithersburg, MD: National Bureau of Standards Workshop.Google Scholar
McMillan, D.J., Baughman, G.D. & Schamber, F.H. (1985). Experience with multiple-least-squares fitting with derivative references. In Microbeam Analysis—1985, Armstrong, J.T. (Ed.), pp. 137140. San Francisco, CA: San Francisco Press.Google Scholar
Schamber, F.H. (1973). A new technique for deconvolution of complex X-ray energy spectra. Proceedings 8th National Conference of Electron Probe Analysis Society of America, New Orleans, LA, Paper 85.Google Scholar
Schamber, F.H. (1977). A modification of the least-squares fitting method which provides continuum suppression. In X-Ray Analysis of Environmental Samples, Dzubay, T.G. (Ed.), pp. 241257. Ann Arbor, MI: Ann Arbor Science Publishers.Google Scholar
Schamber, F.H. (1978). In Proceedings 13th National Conference of the Microbeam Analysis Society, Ann Arbor, Michigan, p. 50.Google Scholar
Schamber, F.H. (1979). Curve fitting techniques and their application to the analysis of energy dispersive spectra. In NBS Special Publication 604: Energy Dispersive X-Ray Spectrometry, Heinrich, K.F.J, Newbury, D.E., Myklebust, R.L. & Fiori, C.E. (Eds.), pp. 193231. Gaithersburg, MD: National Bureau of Standards Workshop.Google Scholar
Schamber, F.H., Wodke, N.F. & McCarthy, J.J. (1977). Least-squares fit with digital filter: The method and its application to EDS spectra. Proceedings of the 12th Annual Conference of Microbeam Analysis Society, Boston, MA.Google Scholar
Statham, P.J. (1974). A comparison of some quantitative techniques for treating energy dispersive X-ray spectra. Proceedings of the 9th Annual Conference of Microbeam Analysis Society, Ottawa, ON, Canada, pp. 21A–21C.Google Scholar
Statham, P.J. (1977). Deconvolution and background subtraction by least-squares fitting with prefiltering of spectra. Anal Chem 49(14), 21492154.CrossRefGoogle Scholar