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Impact of 40 Years of Technology Advances on EDS System Performance

Published online by Cambridge University Press:  06 October 2009

Jon McCarthy ,
John Friel  and
Patrick Camus
Jon McCarthy*
Affiliation:
Materials Science Center, College of Engineering, University of Wisconsin, Madison, WI 53706, USA
John Friel
Affiliation:
Department of Geology, Temple University, Philadelphia, PA 19122, USA
Patrick Camus
Affiliation:
Marketing and Application Group, Thermo Fisher Scientific, 5225 Verona Rd., Madison, WI 53711, USA
*
Corresponding author. E-mail: jjmccarthy@wisc.edu
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Abstract

The rapid advance and falling costs of computing power and data storage during the last 40 years have greatly enhanced the data reduction speed and analytical capacity of energy dispersive spectroscopy (EDS) systems. At the same time, the solid state X-ray detector [until recently, the Si(Li) diode] has seen performance increases due to the use of advanced materials and processing techniques. In addition, the performance of the electronic components (field effect transistor, preamp, and pulse processor) of an EDS system has been constantly improved. These technology advances have resulted in improved spectral quality, excellent light element detection, and increased count rate performance. The results have been truly remarkable and driven by the needs of the analyst. This article will summarize the progress made in these areas in the last 40 years and make a brief reference to prospects for future development in EDS system performance.

Keywords

microbeam analysisX-ray microanalysisenergy dispersive spectroscopySi(Li) detectorFETincomplete charge collectionsilicon drift detectors
Type
Special Section: 40 Years of EDS
Information
Microscopy and Microanalysis , Volume 15 , Issue 6 , December 2009 , pp. 484 - 490
Copyright
Copyright © Microscopy Society of America 2009

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References

REFERENCES

Aden, G. & Issacs, D. (1987). X-ray detector window reveals the light element world. Res Dev 29, 85–90.Google Scholar
Barbi, N.C., Sandborg, A.O., Russ, J.C. & Soderquist, C.C. (1974). Light element analysis on the scanning electron microscope using a windowless energy-dispersive X-ray spectrometer. In Scanning Electron Microscopy 1974, Johari, O. (Ed.), pp. 151–158. Chicago, IL: IITRI.Google Scholar
Burgess, S., Statham, P., Holland, J. & Chou, Y.-H. (2007). Standardless quantitative analysis using a drift detector, what accuracy is possible from live and reconstructed data? Microsc Microanal 13(2yes), 1432–1433.CrossRefGoogle Scholar
Fano, U. (1947). Ionization yield of radiatios. II. The fluctuations of the number of ions. Phys Rev 71(1), 26–29.CrossRefGoogle Scholar
Friel, J.J., Goldstein, J.I., McCarthy, J.J. & Wodke, N.F. (1977). Combined EDS and WDS analysis with an automated electron microprobe. In Proceedings of the 12th Annual Conference of the Microbeam Analysis Society, Heinrich, K.F.J. (Ed.), pp. 50–51. Boston, MA: San Francisco Press.Google Scholar
Gatti, E., Manfredi, P.F., Sampietro, M. & Speziali, V. (1990). Suboptimal filtering of 1/f noise in detector charge measurements. Nucl Instrum Meth A 297(3), 467–478.CrossRefGoogle Scholar
Gauthier, C., Goulon, J., Moguiline, E., Elleaume, P., Feite, S., Gaburro, Z., Longoni, A., Gatti, E., Dressler, P., Lampert, M.O. & Henck, R. (1994). A high-resolution silicon drift chamber for X-ray spectroscopy. Nucl Instrum Meth A 349(1), 258–262.CrossRefGoogle Scholar
Grudberg, P., Warburton, W. & Harris, J. (2002). X-ray spectrometry in the fast lane: An introduction to high speed digital processing techniques and their application to emerging EDS technologies. Microsc Microanal 8(2yes), 76–77.CrossRefGoogle Scholar
Jordanov, V.T. & Knoll, G.F. (1993). Digital pulse processor using a moving average technique. IEEE Trans Nucl Sci 40(4), 764–769.CrossRefGoogle Scholar
Jordanov, V.T., Knoll, G.F., Huber, A.C. & Pantazis, J.A. (1994). Digital techniques for real time pulse shaping in radiation measurement. Nucl Instrum Meth A 353, 261–264.CrossRefGoogle Scholar
Joy, D.C. (1995). Modelling the energy despersive X-ray detector. In X-ray Spectrometry in Electron Beam Instruments, Williams, D.B., Goldstein, J.I. & Newbury, D. (Eds.), pp. 53–65. New York: Plenum Press.CrossRefGoogle Scholar
Kandiah, K., Smith, A.J. & White, G. (1975). A pulse processor for X-ray spectrometry with Si(Li)-detectors. IEEE Trans Nucl Sci 22(5), 2058–2065.CrossRefGoogle Scholar
Kandiah, K. & White, G. (1981). Status Harwell of opto-electronic and time-variant signal processing for high performance nuclear spectroscopy with semiconductor detectors. IEEE Trans Nucl Sci NS-28(1), 613–620.CrossRefGoogle Scholar
Lechner, P., Pahlke, A. & Soltau, H. (2004). Novel high-resolution silicon drift detectors. X-Ray Spectrom 33, 1–6.CrossRefGoogle Scholar
Lund, M.W. (1995). Current trends in Si(Li) detector windows for light element analysis. In X-Ray Spectrometry in Electron Beam Instruments, Williams, D.B., Goldstein, J.I. & Newbury, D. (Ed.), pp. 21–31. New York: Plenum Press.CrossRefGoogle Scholar
McCarthy, J.J. (1995). The effect of detector dead layers on light element detection. In X-ray Spectrometry in Electron Beam Instruments, Williams, D.B., Goldstein, J.I. & Newbury, D. (Eds.), pp. 67–81. New York: Plenum Press.CrossRefGoogle Scholar
McCarthy, J.J. & Friel, J.J. (2002). Wavelength dispersive spectrometer and energy dispersive spectrometer automation: Past and future development. Microsc Microanal 7(2), 150–158.CrossRefGoogle Scholar
McCarthy, J.J. & Schamber, F.H. (1977). A modular microprobe automation system. In 8th International Conference on X-Ray Optics and Microanalysis, Ogilvie, R. (Ed.), pp. 51A–51F. Boston, MA: San Francisco Press.Google Scholar
Mott, R.B. & Friel, J.J. (1995). Improving EDS performance with digital pulse processing. In X-Ray Spectrometry in Electron Beam Instruments, Williams, D.B., Goldstein, J.I. & Newbury, D. (Ed.), pp. 127–157. New York: Plenum Press.CrossRefGoogle Scholar
Nashashibi, T. & White, G. (1990). A low noise FET with integrated charge restoration for radiation detectors. IEEE Trans Nucl Sci 37(2), 452–456.CrossRefGoogle Scholar
Roberts, C. (2003). Improvements to light element X-ray windows for SiLi detectors. Microsc Microanal 9(2yes), 530–531.CrossRefGoogle Scholar
Schamber, F. (2008). 35 Years of EDS software: The more things change, the more they stay the same. Microsc Microanal 14(2yes), 1154–1155.CrossRefGoogle Scholar
Statham, P.J. (1999). Measuring performance of energy-dispersive X-ray system. Microsc Microanal 4, 605–615.CrossRefGoogle Scholar
Statham, P.J. & Nashashibi, T. (1987). The impact of low-noise design on X-ray microanalytical performance. In Microbeam Analysis—1988, Newbury, D.E. (Ed.), pp. 50–54. San Francisco, CA: San Francisco Press.Google Scholar
Struder, L. (1998). High resolution nondispersive X-ray spectrometry with state-of-the-art silicon detectors. Mikrochem Acta 15yes, 10–19.Google Scholar
Zulliger, H.R. & Aitken, D.W. (1970). Fano factor fact and fallacy. IEEE Trans Nucl Sci NS-17, 187–195.CrossRefGoogle Scholar