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Matrix Effects in the Energy Dispersive X-Ray Analysis of CaO-Al2O3-MgO Inclusions in Steel

Published online by Cambridge University Press:  04 November 2011

Petrus Christiaan Pistorius  and
Neerav Verma
Petrus Christiaan Pistorius*
Affiliation:
Carnegie Mellon University, Department of Materials Science and Engineering, 5000 Forbes Avenue, Pittsburgh, PA 15213, USA
Neerav Verma
Affiliation:
Carnegie Mellon University, Department of Materials Science and Engineering, 5000 Forbes Avenue, Pittsburgh, PA 15213, USA
*
Corresponding author. E-mail: pistorius@cmu.edu
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Abstract

Energy dispersive X-ray microanalysis of micron-sized inclusions in steel is of considerable industrial importance. Measured spectra and Monte Carlo simulations show a significant effect of the steel matrix on analysis of CaO-Al2O3-MgO inclusions: the steel matrix filters the softer (Al and Mg) characteristic X-rays, increasing the relative height of the Ca peak. Bulk matrix correction methods would not result in correct inclusion compositions, but operating at a lower acceleration voltage shifts the effect to smaller inclusion sizes.

Keywords

energy dispersive X-ray (EDX)scanning electron microscope (SEM)steelinclusionsMonte Carlosimulation
Type
Materials Applications
Information
Microscopy and Microanalysis , Volume 17 , Issue 6 , December 2011 , pp. 963 - 971
Copyright
Copyright © Microscopy Society of America 2011

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References

REFERENCES

Altay, A., Carter, C.B., Rulis, P., Ching, W.Y., Arslan, I. & Gülgün, M.A. (2010). Characterizing CA2 and CA6 using ELNES. J Solid State Chem 183, 1776–1784.CrossRefGoogle Scholar
Armstrong, J.T. (1991). Quantitative elemental analysis of individual microparticles with electron beam instruments. In Electron Probe Quantitation, Heinrich, K.F.J. & Newbury, D.E. (Eds.), pp. 261–315. New York: Plenum Press.CrossRefGoogle Scholar
Armstrong, J.T. & Buseck, P.R. (1975). Quantitative chemical analysis of individual microparticles using the electron microprobe: Theoretical. Anal Chem 47, 2178–2192.CrossRefGoogle Scholar
ASTM (2008). Standard test methods for rating and classifying inclusions in steel using the scanning electron microscope. ASTM Standard E2142-08. West Conshohocken, PA: ASTM International.Google Scholar
Bennett, S. (2010). Kaye & Laby Tables of Physical & Chemical Constants, 16th ed. Available at www.kayelaby.npl.co.uk; last visited November 2010.Google Scholar
Drouin, D., Couture, A.R., Joly, D., Tastet, X., Aimez, V. & Gauvin, R. (2007). CASINO V2.42—A fast and easy-to-use modeling tool for scanning electron microscopy and microanalysis users. Scanning 29, 92–101.CrossRefGoogle ScholarPubMed
Goldstein, J.I., Newbury, D.E., Joy, D.C., Lyman, C.E., Echlin, P., Lifshin, E., Sawyer, L. & Michael, J.R. (2003). Scanning Electron Microscopy and X-ray Microanalysis. 3rd ed. New York: Kluwer Academic.CrossRefGoogle Scholar
Haynes, W.M. (2010). CRC Handbook of Chemistry and Physics, 91st ed.Cleveland, OH: CRC Press.Google Scholar
Hubbell, J.H. & Seltzer, S.M. (2004). Tables of X-Ray Mass Attenuation Coefficients and Mass Energy-Absorption Coefficients (version 1.4). Available at www.physics.nist.gov/xaamdi (Last visited March 23, 2011). Gaithersburg, MD: National Institute of Standards and Technology.Google Scholar
Iyi, N., Göbbels, M. & Matsui, Y. (1995). The Al-rich part of the system CaO-Al2O3-MgO. Part II. Structural refinement of two new magnetoplumbite-related phases. J Solid State Chem 120, 364–371.CrossRefGoogle Scholar
Peterson, R.C., Lager, G.A. & Hitterman, R.L. (1991). A time-of-flight neutron powder diffraction study of MgAl2O4 at temperatures up to 1273K. Am Mineral 76, 1455–1458.Google Scholar
Pouchou, J.-L. & Pichoir, F. (1991). Quantitative analysis of homogeneous or stratified microvolumes applying the model “PAP.” In Electron Probe Quantitation, Heinrich, K.F.J. & Newbury, D.E. (Eds.), pp. 31–75. New York: Plenum Press.CrossRefGoogle Scholar
Pretorius, E.B., Oltmann, H.G. & Cash, T. (2010). The effective modification of spinel inclusions by Ca treatment in LCAK steel. Iron Steel Technol 7(7), 31–44.Google Scholar
Ritchie, N.W.M. (2009). Spectrum simulation in DTSA-II. Microsc Microanal 15, 454–468.CrossRefGoogle ScholarPubMed
Salvat, F., Escuder, J.A., Bote, D. & Llovet, X. (2007). Simulation of EPMA spectra using PENELOPE. Microsc Microanal 13(S2), 1388–1389.CrossRefGoogle Scholar
Story, S.R., Gupta, N., Casuccio, G.S. & Potter, M.S. (2010). Analysis of Ti-, Mg-, and Zr-bearing inclusions in ultra-low and low carbon steels. In AISTech 2010 Proceedings, vol. II, pp. 1–10. Warrendale, PA: Association for Iron & Steel Technology.Google Scholar
Story, S.R., Piccone, T.J. & Fruehan, R.J. (2004). Inclusion analysis to predict casting behavior. Iron Steel Technol 1(9), 163–169.Google Scholar
Taş, A.T. (1998). Chemical preparation of the binary compounds in the calcia–alumina system by self-propagating combustion synthesis. J Am Ceram Soc 81, 2853–2863.CrossRefGoogle Scholar
Verma, N., Lind, M., Pistorius, P.C., Fruehan, R.J. & Potter, M. (2010). Modification of spinel inclusions by calcium in liquid steel. Iron Steel Technol 7(7), 189–197.Google Scholar
Wang, Y., Valdez, M. & Sridhar, S. (2002). Formation of CaS on Al2O3-CaO inclusions during solidification of steels. Metall Mater Trans B 33B, 625–632.CrossRefGoogle Scholar
Werlefors, T. & Ekelund, S. (1978). Automatic multiparameter characterization of non-metallic inclusions—An evaluation of the PASEM. Scand J Metall 7, 60–70.Google Scholar