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The Backscatter Electron Signal as an Additional Tool for Phase Segmentation in Electron Backscatter Diffraction

Published online by Cambridge University Press:  10 April 2013

E.J. Payton  and
G. Nolze
E.J. Payton*
Affiliation:
Federal Institute for Materials Research and Testing, 12205 Berlin, Germany
G. Nolze
Affiliation:
Federal Institute for Materials Research and Testing, 12205 Berlin, Germany
*
*Corresponding author. E-mail: eric.payton@bam.de
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Abstract

The advent of simultaneous energy dispersive X-ray spectroscopy (EDS) data collection has vastly improved the phase separation capabilities for electron backscatter diffraction (EBSD) mapping. A major problem remains, however, in distinguishing between multiple cubic phases in a specimen, especially when the compositions of the phases are similar or their particle sizes are small, because the EDS interaction volume is much larger than that of EBSD and the EDS spectra collected during spatial mapping are generally noisy due to time limitations and the need to minimize sample drift. The backscatter electron (BSE) signal is very sensitive to the local composition due to its atomic number (Z) dependence. BSE imaging is investigated as a complimentary tool to EDS to assist phase segmentation and identification in EBSD through examination of specimens of meteorite, Cu dross, and steel oxidation layers. The results demonstrate that the simultaneous acquisition of EBSD patterns, EDS spectra, and the BSE signal can provide new potential for advancing multiphase material characterization in the scanning electron microscope.

Keywords

electron backscatter diffraction (EBSD)energy dispersive X-ray spectroscopy (EDS)scanning electron microscope (SEM)multiphase microstructurephase identificationsegmentationbackscatter electron imaging (BSE)meteoriteMonte Carlo simulation
Type
EBSD Special Section
Information
Microscopy and Microanalysis , Volume 19 , Issue 4 , August 2013 , pp. 929 - 941
Copyright
Copyright © Microscopy Society of America 2013 

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References

Bachmann, F., Hielscher, R. & Schaeben, H. (2010). Texture analysis with MTEX—Free and open source software toolbox. Solid State Phenom 160, 63–68.Google Scholar
Berger, D. & Niedrig, H. (1999). Complete angular distribution of electrons backscattered from tilted multicomponent specimens. Scanning 21, 187–190.Google Scholar
Büchner, A.R. (1973). Determination of the mean atomic number of alloys in quantitative microprobe analysis. Arch Eisenhüttenwes 44, 143–147.CrossRefGoogle Scholar
Day, A. (1993). Developments in the EBSP technique and their application to grain imaging. PhD Thesis. Bristol, UK: Bristol University. Google Scholar
Dingley, D.J. & Wright, S.I. (2009). Phase identification through symmetry determination in EBSD patterns. In Electron Backscatter Diffraction in Materials Science, 2nd ed., Schwartz, A.J., Kumar, M., Adams, B.L. & Field, D.P. (Eds.), pp. 97–107. New York: Springer Science and Business Media.CrossRefGoogle Scholar
Donovan, J.J. (2011). An update on electron backscatter and mass effect. Available at http://epmalab.uoregon.edu/BSE.htm (accessed February 7, 2012).Google Scholar
Donovan, J.J., Pingitore, N.E. & Westphal, A. (2003). Compositional averaging of backscatter intensities in compounds. Microsc Microanal 9, 202–215.Google Scholar
Dziaszyk, S. (2010). Gefügecharakterisierung von Mehrphasenstählen mittels Orientierungsmikroskopie und Nanoindentierung. PhD Dissertation. Bochum, Germany: Ruhr-Universität Bochum. Google Scholar
El-Dasher, B. & Deal, A. (2009). Application of electron backscatter diffraction to phase identification. In Electron Backscatter Diffraction in Materials Science, 2nd ed., Schwartz, A.J., Kumar, M., Adams, B.L. & Field, D.P. (Eds.), pp. 81–95. New York: Springer Science and Business Media.Google Scholar
Fandrich, R., Gu, Y., Burrows, D. & Moeller, K. (2007). Modern SEM-based mineral liberation analysis. Int J Miner Proc 84, 310–320.Google Scholar
Goldstein, J., Newbury, D.E., Joy, D.C., Lyman, C.E., Echlin, P., Lifshin, E., Sawyer, L. & Michael, J.R. (Eds.). (2007). Scanning Electron Microscopy and X-Ray Microanalysis, 3rd ed. New York: Kluwer Academic/Plenum Publishers.Google Scholar
Harding, D.P. (2002). Mineral identification using a scanning electron microscope. Miner Metall Proc 19, 215–219.Google Scholar
Kranzmann, A., Neddemeyer, T., Ruhl, A.S., Huenert, D., Bettge, D., Oder, G. & Neumann, R.S. (2011). The challenge in understanding the corrosion mechanisms under oxyfuel combustion conditions. Int J Greenh Gas Con 5(Suppl 1), S168–S178.Google Scholar
Lloyd, G.E. (1987). Atomic number and crystallographic contrast images with the SEM: A review of backscattered electron techniques. Mineral Mag 51, 3–19.CrossRefGoogle Scholar
Newbury, D.E. & Ritchie, N.W.M. (2011). Can X-ray spectrum imaging replace backscattered electrons for compositional contrast in the scanning electron microscope? Scanning 33, 174–192.Google Scholar
Nowell, M.M. & Wright, S.I. (2004). Phase differentiation via combined EBSD and XEDS. J Microsc 213, 296–305.Google Scholar
Pinard, P.T., Lagacé, M., Hovington, P., Thibault, D. & Gauvin, R. (2011). An open-source engine for the processing of electron backscatter patterns: EBSD-Image. Microsc Microanal 17, 374–385.CrossRefGoogle ScholarPubMed
Prior, D.J., Boyle, A.P., Brenker, F., Cheadle, M.C., Day, A., Lopez, G., Peruzzi, L., Potts, G., Reddy, S., Spiess, R., Timms, N.E., Trimby, P., Wheeler, J. & Zetterstrom, L. (1999). The application of electron backscatter diffraction and orientation contrast imaging in the SEM to textural problems in rocks. Am Mineral 84, 1741–1759.CrossRefGoogle Scholar
Prior, D.J., Trimby, P.W., Weber, U.D. & Dingley, D.J. (1996). Orientation contrast imaging of microstructures in rocks using forescatter detectors in the scanning electron microscope. Mineral Mag 60, 859–869.CrossRefGoogle Scholar
Ritchie, N.W.M. (2005). A new Monte Carlo application for complex sample geometries. Surf Interface Anal 37, 1006–1011.CrossRefGoogle Scholar
Ritchie, N.W.M. (2009). Spectrum simulation in DTSA-II. Microsc Microanal 15, 454–468.Google Scholar
Ryde, L. (2006). Application of EBSD to analysis of microstructures in commercial steels. Mater Sci Tech 22, 1297–1306.Google Scholar
Schneider, C.L., Neumann, R. & Alcover-Neto, A. (2004). Automated, adaptive thresholding procedure for mineral sample images generated by BSE detector. In Applied Mineralogy: Developments in Science and Technology—Proceedings ICAM 2004, Pecchio, M., Andrade, F.R.D. de, D'Agostino, L.Z., Kahn, H., Sant'Agostino, L.M. & Tassinari, M.M.M.L. (Eds.), pp. 103–106. São Paulo, Brazil: International Council for Applied Mineralogy.Google Scholar
Schwartz, A.J., Kumar, M. & Adams, B.L. (Eds.) (2000). Electron Backscatter Diffraction in Materials Science, 1st ed. New York: Kluwer Academic.Google Scholar
Schwarzer, R.A., Field, D.P., Adams, B.L., Kumar, M. & Schwartz, A.J. (2009). Present state of electron backscatter diffraction and prospective developments. In Electron Backscatter Diffraction in Materials Science, 2nd ed., Schwartz, A.J., Kumar, M., Adams, B.L. & Field, D.P. (Eds.), pp. 1–20. New York: Springer Science and Business Media.Google Scholar
Tak, K.-G., Schulz, U. & Eggeler, G. (2009). On the effect of micrograin crystallography on creep of FeCr alloys. Mater Sci Eng A 510–511, 121–129.Google Scholar
Wells, O.C., Gignac, L.M., Murray, C.E., Frye, A. & Bruley, J. (2006). Use of backscattered electron detector arrays for forming backscattered electron images in the scanning electron microscope. Scanning 28, 27–31.CrossRefGoogle ScholarPubMed
Wernicke, A., Joost, R., Ehlert, U.-D., Ciampa, M., Hardelin, J., Falappa, A., Quiñones, M., Antl, I., Ji-Hui, C., Shmyrev, N., Bernharsson, A., Nylander, D., Stawiarska, P., Stuestøl, K., Pitonyak, A. & SimaMoto, R. (2010). GNU Image Manipulation Program: User manual. Available at http://www.gimp.org/ (accessed August 31, 2012).Google Scholar
Wilkinson, A.J. & Hirsch, P.B. (1997). Electron diffraction based techniques in scanning electron microscopy of bulk materials. Micron 28, 279–308.Google Scholar
Wilson, A. & Spanos, G. (2001). Application of orientation imaging microscopy to study phase transformations in steels. Mater Charact 46, 407–418.Google Scholar
Winkelmann, A., Trager-Cowan, C., Sweeney, F., Day, A.P. & Parbrook, P. (2007). Many-beam dynamical simulation of electron backscatter diffraction patterns. Ultramicroscopy 107, 414–421.CrossRefGoogle ScholarPubMed
Wright, S.I. & Nowell, M.M. (2006). EBSD image quality mapping. Microsc Microanal 12, 72–84.Google Scholar
Wu, J., Wray, P.J., Garcia, C.I., Hua, M. & Deardo, A.J. (2005). Image quality analysis: A new method of characterizing microstructures. ISIJ Int 45, 254–262.Google Scholar
Zupanič, F. (2010). Extracting electron backscattering coefficients from backscattered electron micrographs. Mater Charact 61, 1335–1341.Google Scholar
Zupanič, F., Bončina, T. & Markoli, B. (2010). Use of electron backscattering coefficients for identification of Be-bearing phases. In Microscopy: Science, Technology, Applications and Education, vol. 3, Mendez-Vilas, A. & Diaz, J. (Eds.), pp. 1824–1829. Badajoz, Spain: Formatex Research Center.Google Scholar