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Overcoming Peak Overlaps in Titanium- and Vanadium-Bearing Materials with Multiple Linear Least Squares Fitting

Published online by Cambridge University Press:  10 March 2017

Michael Mengason*
Affiliation:
National Institute of Standards and Technology, Gaithersburg, MD, USA
Nicholas Ritchie
Affiliation:
National Institute of Standards and Technology, Gaithersburg, MD, USA
*
*Corresponding author.michael.mengason@nist.gov
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Abstract

The evolution of the energy dispersive spectrometer (EDS) from the lithium-drifted silicon detector [Si(Li)] to the silicon drift detector (SDD) has created new opportunities in the field of electron probe X-ray microanalysis. The SDD permits operation at significantly higher count rates than the Si(Li) and also provides a more stable energy scale. X-ray spectra captured by EDS can now be analyzed qualitatively or quantitatively under the same beam conditions as used for wavelength dispersive spectrometry (WDS). Standards-based quantitative EDS (SB-Quant-EDS) can thus provide analyses that are accurate and precise for an ever growing number of materials measurement problems. In this study, we analyze NIST research glasses with “known” nominal concentrations of titanium (Ti) and vanadium (V) to evaluate the external reproducibility of the SB-Quant-EDS technique in the presence of severe peak overlaps. We additionally analyze several naturally occurring oxide minerals by WDS and EDS simultaneously and evaluate the outputs of these two methods when quantifying the same analytical volume within the sample.

Type
Materials Science Applications
Copyright
© Microscopy Society of America 2017 

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References

Armstrong, J. (2014). Comparative performance of SDD-EDS and WDS detectors for quantitative analysis of mineral specimens: The next generation electron microprobe. Microsc Microanal 20(Suppl 3), 692693.CrossRefGoogle Scholar
Boettinger, W.J., Newbury, D.E., Wang, K., Bendersky, L.A., Chiu, C., Kattner, U.R., Young, K. & Chao, B. (2010). Examination of multiphase (Zr,Ti) (V,Cr,Mn,Ni)2 Ni-NH electrode alloys: Part I. Dendritic solidification structure. Metall Mater Trans A 41(8), 20332047.CrossRefGoogle Scholar
Donachie, M.J. (2000). Titanium: A Technical Guide, 2nd ed, pp. 5557. Materials Park, Ohio, USA: ASM International.CrossRefGoogle Scholar
Donovan, J.J., Kremser, D. & Fournelle, J.H. (2012). Probe for EPMA: Acquisition, Automation, and Analysis, Version 11.4.5. Eugene, Oregon: Probe Software, Inc www.probesoftware.com.Google Scholar
Goldstein, J., Newbury, D., Joy, D., Lyman, C., Echlin, P., Lifshin, E., Sawyer, L. & Michael, J.R. (2003). Scanning Electron Microscopy and X-ray Microanalysis, 3rd ed., New York, NY: Springer Science + Business Media, Inc.CrossRefGoogle Scholar
Gopon, P., Fournelle, J., Sobol, P. & Llovet, X. (2013). Low-voltage electron-probe microanalysis of Fe-Si compounds using soft X-rays. Microsc Microanal 19, 16981708.CrossRefGoogle ScholarPubMed
Newbury, D.E. & Ritchie, N.W.M. (2015). Performing elemental microanalysis with high accuracy and high precision by scanning electron microscopy/silicon drift detector energy-dispersive X-ray spectrometry (SEM/SDD-EDS). J Mater Sci 50, 493518.CrossRefGoogle ScholarPubMed
Newbury, D.E. & Ritchie, N.W.M. (2016). Measurement of trace constitutes by electron-exited X-ray microanalysis with energy-dispersive spectrometry. Microsc Microanal 22, 520535.CrossRefGoogle Scholar
Pistorius, P.C. & Verma, N. (2011). Matrix effects in the energy dispersive X-ray analysis of CaO-Al2O3-MgO inclusions in steel. Microsc Microanal 17, 963971.CrossRefGoogle ScholarPubMed
Rack, H. & Qazi, J. (2006). Titanium alloys for biomedical applications. Mater Sci Eng C 26(8), 12691277.CrossRefGoogle Scholar
Ritchie, N.W.M. (2011). Standards-based quantification in DTSA-II—Part 1. Microscopy Today 19, 3036.CrossRefGoogle Scholar
Ritchie, N.W.M. (2015). NIST DTSA II public domain software, version: Iona 2016-04-25. National Institute of Standards and Technology. Available at http://www.cstl.nist.gov/div837/837.02/epq/dtsa2/index.html (retrieved April 25, 2016).Google Scholar
Ritchie, N.W.M. & Newbury, D.E. (2012). Uncertainty estimates for electron probe X-ray microanalysis measurements. Anal Chem 84(22), 99569962.CrossRefGoogle ScholarPubMed
Ritchie, N.W.M., Newbury, D.E. & Davis, J.M. (2012). EDS measurements of X-ray intensity at WDS precision and accuracy using a silicon drift detector. Microsc Microanal 18, 892904.CrossRefGoogle ScholarPubMed
Schamber, F.H. (1997). A modification of the linear least-squares fitting method which provides continuum suppression. In X-Ray Fluorescence Analysis of Environmental Samples, Dzubay, T.G. (Ed.), pp. 241257. Ann Arbor, MI: Ann Arbor Science Publishers.Google Scholar
US Geological Survey (2016). Mineral Commodity Summaries 2016: U.S. Geological Survey, 202 p. https://doi.org//10.3133/70140094.Google Scholar