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A Tool for Local Thickness Determination and Grain Boundary Characterization by CTEM and HRTEM Techniques

Published online by Cambridge University Press:  24 March 2015

Ákos K. Kiss
Affiliation:
Hungarian Academy of Sciences, Research Center for Natural Sciences, Institute for Technical Physics and Materials Science, Konkoly Thege M. út 29-33, H-1121 Budapest, Hungary Doctoral School of Molecular- and Nanotechnologies, Faculty of Information Technology, University of Pannonia, Egyetem u. 10, H-8200 Veszprém, Hungary
Edgar F. Rauch
Affiliation:
SIMaP, Grenoble INP/CNRS, 1130 rue de la Piscine, BP 75, F-38402 St Martin D’Heres, France
Béla Pécz
Affiliation:
Hungarian Academy of Sciences, Research Center for Natural Sciences, Institute for Technical Physics and Materials Science, Konkoly Thege M. út 29-33, H-1121 Budapest, Hungary
János Szívós
Affiliation:
Hungarian Academy of Sciences, Research Center for Natural Sciences, Institute for Technical Physics and Materials Science, Konkoly Thege M. út 29-33, H-1121 Budapest, Hungary Doctoral School of Molecular- and Nanotechnologies, Faculty of Information Technology, University of Pannonia, Egyetem u. 10, H-8200 Veszprém, Hungary
János L. Lábár*
Affiliation:
Hungarian Academy of Sciences, Research Center for Natural Sciences, Institute for Technical Physics and Materials Science, Konkoly Thege M. út 29-33, H-1121 Budapest, Hungary
*
*Corresponding author. [email protected]
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Abstract

A new approach for measurement of local thickness and characterization of grain boundaries is presented. The method is embodied in a software tool that helps to find and set sample orientations useful for high-resolution transmission electron microscopic (HRTEM) examination of grain boundaries in polycrystalline thin films. The novelty is the simultaneous treatment of the two neighboring grains and orienting both grains and the boundary plane simultaneously. The same metric matrix-based formalism is used for all crystal systems. Input into the software tool includes orientation data for the grains in question, which is determined automatically for a large number of grains by the commercial ASTAR program. Grain boundaries suitable for HRTEM examination are automatically identified by our software tool. Individual boundaries are selected manually for detailed HRTEM examination from the automatically identified set. Goniometer settings needed to observe the selected boundary in HRTEM are advised by the software. Operation is demonstrated on examples from cubic and hexagonal crystal systems.

Type
Materials Applications
Copyright
© Microscopy Society of America 2015 

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References

Diamond, R. (2001). Molecular modelling and graphics. In International Tables for Crystallography, vol. B, 2nd ed. Shmueli, U. (Ed.), p. 360. Dordrecht, Boston, MA, and London: Kluwer Academic Publishers.Google Scholar
Dingley, D.J. (2006). Orientation imaging microscopy for the transmission electron microscope. Microchim Acta 155, 1929.Google Scholar
Duden, T., Gautam, A. & Dahmen, U. (2011). KSpaceNavigator as a tool for computer-assisted sample tilting in high-resolution imaging, tomography and defect analysis. Ultramicroscopy 111, 15741580.Google Scholar
Edington, J.W. (1975). 2 Electron Diffraction in the Electron Microscope. Eindhoven: N. V. Phillips’ Gloeilampenfabriken.Google Scholar
Edington, J.W. (1976). 4 Typical Electron Microscope Investigations. Eindhoven: N. V. Phillips’ Gloeilampenfabriken.CrossRefGoogle Scholar
Egerton, R.F. (2011). Electron Energy-Loss Spectroscopy in the Electron Microscope, 3rd ed. New York, NY, Dordrecht, Heidelberg, and London: Springer Science+Business Media.CrossRefGoogle Scholar
Egerton, R.F., Li, P. & Malac, M. (2004). Radiation damage in the TEM and SEM. Micron 35, 399409.Google Scholar
Forwood, C.T. & Clarebrough, L.M. (1991). Electron Microscopy of Interfaces in Metals and Alloys. Bristol and New York: IOP Publishing. p. 113. (figure 4.8).Google Scholar
Gontard, L.C., Dunin-Borkowski, R.E. & Ozkaya, D. (2008). Three-dimensional shapes and spatial distributions of Pt and PtCr catalyst nanoparticles on carbon black. J Microsc 232, 248259.Google Scholar
Gorelik, T.E., Stewart, A.A. & Kolb, U. (2011). Structure solution with automated electron diffraction tomography data: Different instrumental approaches. J Microsc 244, 325331.Google Scholar
Grimmer, H., Bollmann, W. & Warrington, D.H. (1974). Coincidence-site lattices and complete pattern-shift in cubic crystals. Acta Crystallogr A 30, 197207.Google Scholar
Habas, S.E., Lee, H., Radmilovic, V., Somorjai, G.A. & Yang, P. (2007). Shaping binary metal nanocrystals through epitaxial seeded growth. Nat Mater 6, 692697.CrossRefGoogle ScholarPubMed
Hovmöller, S. (2008). Electron Rotation Camera. Patent WO 2008/060237. http://www.freepatentsonline.com/WO2008060237.html.Google Scholar
Jinschek, J.R., Batenburg, K.J., Calderon, H.A., Kilaas, R., Radmilovic, V. & Kisielowski, C. (2008). 3-D reconstruction of the atomic positions in a simulated gold nanocrystal based on discrete tomography: Prospects of atomic resolution electron tomography. Ultramicroscopy 108, 589604.Google Scholar
Kelly, P.M., Jostsons, A., Blake, R.G. & Napier, J.G. (1975). The determination of foil thickness by scanning transmission electron microscopy. Phys Status Solidi 31(2), 771780.CrossRefGoogle Scholar
Kiss, Á.K. & Lábár, J.L. (2013). A method for complete characterization of the macroscopic geometry of grain boundaries. Mater Sci Forum 729, 97102.Google Scholar
Kolb, U., Gorelik, T., Kübel, C., Otten, M.T. & Hubert, D. (2007). Towards automated diffraction tomography: Part I—Data acquisition. Ultramicroscopy 107, 507513.Google Scholar
Kolb, U., Gorelik, T. & Otten, M.T. (2008). Towards automated diffraction tomography. Part II—Cell parameter determination. Ultramicroscopy 108, 763772.Google Scholar
Kolb, U., Mugnaioli, E. & Gorelik, T.E. (2011). Automated electron diffraction tomography—A new tool for nano crystal structure analysis. Cryst Res Technol 46, 542554.Google Scholar
Ku, H.H. (1966). Notes on the use of propagation of error formulas. J Res NBS C Eng Inst 70(4), 263273.Google Scholar
Lábár, J.L. (2005). Consistent indexing of a (set of) single crystal SAED pattern(s) with the ProcessDiffraction program. Ultramicroscopy 103(3), 237249.CrossRefGoogle ScholarPubMed
Lábár, J.L., Kiss, Á.K., Christiansen, S. & Falk, F. (2012). Characterization of grain boundary geometry in the TEM, exemplified in Si thin films. Solid State Phenom 186, 712.Google Scholar
Li, X.Z. (2004). JECP/SP: A computer program for generating stereographic projections, applicable to specimen orientation adjustment in TEM experiments. J Appl Crystallogr 37(3), 506507.Google Scholar
Lloyd, G.E., Farmer, A. & Mainprice, D. (1997). Misorientation analysis and the formation and orientation of subgrain and grain boundaries. Tectonophysics 279, 5578.Google Scholar
Loretto, M.H. & Smallman, R.E. (1975). Defect Analysis in Electron Microscopy. London: Chapman and Hall Ltd.Google Scholar
Murr, L.E. (1973). Twin boundary energetics in pure aluminium. Acta Metall 21(6), 791797.Google Scholar
Otten, M.T. (1996). SmartTilt: The sensible way of tilting. Proceedings of the Annual Meeting – Electron Microscopy Society of America, 8, 452453.Google Scholar
Pozsgai, I. (1997). The determination of foil thickness by scanning transmission electron microscopy. Ultramicroscopy 68(1), 6975.Google Scholar
Randle, V. (1993). The Measurement of Grain Boundary Geometry. London: The Institute of Physics Publishing. (eq. 2.17).Google Scholar
Randle, V. (2001). A methodology for grain boundary plane assessment by single-section trace analysis. Scripta Mater 44, 27892794.CrossRefGoogle Scholar
Rauch, E.F., Véron, M., Portillo, J., Bultreys, D., Maniette, Y. & Nicolopoulos, S. (2008). Automatic crystal orientation and phase mapping in TEM by precession diffraction. Microsc Microanal 22(6), S5S8.Google Scholar
Saylor, D.M., El-Dasher, B.S., Adams, B.L. & Rohrer, G.S. (2004). Measuring the five-parameter grain-boundary distribution from observations of planar sections. Metall Mater Trans A 35, 19811989.CrossRefGoogle Scholar
Saylor, D.M., Morawiec, A. & Rohrer, G.S. (2003). Distribution of grain boundaries in magnesia as a function of five macroscopic parameters. Acta Mater 51, 36633674.Google Scholar
Schwarzer, R.A. & Sukkau, J. (1998). Automated crystal orientation mapping (ACOM) with a computer controlled TEM by interpreting transmission Kikuchi patterns. Mater Sci Forum 273–275, 215222.Google Scholar
Spence, J.C.H. & Zuo, J.M. (1992). Electron Diffraction. New York, NY: Plenum Press. (Appendix 3.7).Google Scholar
Stadelmann, P.A. (1987). EMS—A software package for electron diffraction analysis and HREM image simulation in materials science. Ultramicroscopy 21, 131146.Google Scholar
Van Aert, S., Batenburg, K.J., Rossell, M.D., Erni, R. & Van Tendeloo, G. (2011). Three-dimensional atomic imaging of crystalline nanoparticles. Nature 470, 374377.Google Scholar
Wan, W., Sun, J., Su, J., Hovmöller, S. & Zou, X. (2013). Three-dimensional rotation electron diffraction: Software RED for automated data collection and data processing. J Appl Crystallogr 46(6), 18631873.CrossRefGoogle ScholarPubMed
Wang, L. (1993). Computer control of the electron microscope sample stage. US Patent, US 5179280 A.Google Scholar
Wu, G. & Zaefferer, S. (2009). Advances in TEM orientation microscopy by combination of dark-field conical scanning and improved image matching. Ultramicroscopy 109, 13171325.Google Scholar
Zaefferer, S. (2000). New developments of computer-aided crystallographic analysis in transmission electron microscopy. J Appl Crystallogr 33, 1025.Google Scholar