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Practical Aspects of Removing the Effects of Elastic and Thermal Diffuse Scattering from Spectroscopic Data for Single Crystals

Published online by Cambridge University Press:  23 April 2014

Nathan R. Lugg ,
Melissa J. Neish ,
Scott D. Findlay  and
Leslie J. Allen
Nathan R. Lugg
Affiliation:
School of Physics, The University of Melbourne, Parkville, Victoria 3010, Australia Institute of Engineering Innovation, The University of Tokyo, Tokyo, 116-0013, Japan
Melissa J. Neish
Affiliation:
School of Physics, The University of Melbourne, Parkville, Victoria 3010, Australia
Scott D. Findlay
Affiliation:
School of Physics, Monash University, Clayton, Victoria 3800, Australia
Leslie J. Allen*
Affiliation:
School of Physics, The University of Melbourne, Parkville, Victoria 3010, Australia
*
*Corresponding author. lja@unimelb.edu.au
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Abstract

A method to remove the effects of elastic and thermal diffuse scattering (TDS) of the incident electron probe from electron energy-loss and energy-dispersive X-ray spectroscopy data for atomically resolved spectrum images of single crystals of known thickness is presented. By calculating the distribution of the probe within a specimen of known structure, it is possible to deconvolve the channeling of the probe and TDS from experimental data by reformulating the inelastic cross-section as an inverse problem. In electron energy-loss spectroscopy this allows valid comparisons with first principles fine-structure calculations to be made. In energy-dispersive X-ray spectroscopy, direct compositional analyses such as ζ-factor and Cliff–Lorimer k-factor analysis can be performed without the complications of channeling and TDS. We explore in detail how this method can be incorporated into existing multislice programs, and demonstrate practical considerations in implementing this method using a simulated test specimen. We show the importance of taking into account the scattering of the probe in k-factor analysis in a zone axis orientation. The applicability and limitations of the method are discussed.

Keywords

scanning transmission electron microscopy (STEM)electron energy-loss spectroscopy (EELS)energy-dispersive X-ray spectroscopy (EDX)channeling and thermal diffuse scattering
Type
FEMMS Special Issue
Information
Microscopy and Microanalysis , Volume 20 , Issue 4 , August 2014 , pp. 1078 - 1089
Copyright
© Microscopy Society of America 2014 

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References

Allen, L.J., D’Alfonso, A.J., Freitag, B. & Klenov, D.O. (2012). Chemical mapping at atomic resolution using energy-dispersive X-ray spectroscopy. MRS Bull 37, 47–52.Google Scholar
Bocher, L., Popova, E., Nolan, M., Gloter, A., Chikoidze, E., March, K., Warot-Fonrose, B., Berini, B., Stéphan, O., Keller, N. & Dumont, Y. (2013). Direct evidence of Fe2+-Fe3+ charge ordering in the ferrimagnetic hematite-ilmenite Fe1.35Ti0.65O3-δ thin films. Phys Rev Lett 111, 167202.Google Scholar
Bosman, M., Keast, V.J., García-Muñoz, J.L., D’Alfonso, A.J., Findlay, S.D. & Allen, L.J. (2007). Two-dimensional mapping of chemical information at atomic resolution. Phys Rev Lett 99, 086102.Google Scholar
Chu, M.-W., Liou, S.C., Chang, C.-P., Choa, F.-S. & Chen, C.H. (2010). Emergent chemical mapping at atomic-column resolution by energy-dispersive X-ray spectroscopy in an aberration-corrected electron microscope. Phys Rev Lett 104, 196101.Google Scholar
Cliff, G. & Lorimer, G.W. (1975). The quantitative analysis of thin specimens. J. Microsc 103, 203–207.Google Scholar
Cover, T. & Thomas, J. (1991). Elements of Information Theory. New York, NY, USA: Wiley Interscience.Google Scholar
D’Alfonso, A.J., Freitag, B., Klenov, D. & Allen, L.J. (2010). Atomic-resolution chemical mapping using energy-dispersive X-ray spectroscopy. Phys Rev B 81, 100101.CrossRefGoogle Scholar
Dwyer, C. & Etheridge, J. (2003). Scattering of Å-scale electron probes in silicon. Ultramicroscopy 96, 343–360.CrossRefGoogle ScholarPubMed
Dwyer, C., Maunders, C., Zheng, C.L., Weyland, M., Tiemeijer, P.C. & Etheridge, J. (2012). Sub-0.1 nm-resolution quantitative scanning transmission electron microscopy without adjustable parameters. Appl Phys Lett 100(19), 191915.Google Scholar
Findlay, S.D., Oxley, M.P. & Allen, L.J. (2008). Modeling atomic-resolution scanning transmission electron microscopy images. Microsc Microanal 14(1), 48–59.Google Scholar
Forbes, B.D., D’Alfonso, A.J., Williams, R.E.A., Srinivasan, R., Fraser, H.L., McComb, D.W., Freitag, B., Klenov, D.O. & Allen, L.J. (2012). Contribution of thermally scattered electrons to atomic resolution elemental maps. Phys Rev B 86, 024108.Google Scholar
Forbes, B.D., Martin, A.V., Findlay, S.D., D’Alfonso, A.J. & Allen, L.J. (2010). Quantum mechanical model for phonon excitation in electron diffraction and imaging using a Born-Oppenheimer approximation. Phys Rev B 82, 104103.Google Scholar
Gazquez, J., Luo, W., Oxley, M.P., Prange, M., Torija, M.A., Sharma, M., Leighton, C., Pantelides, S.T., Pennycook, S.J. & Varela, M. (2011). Atomic-resolution imaging of spin-state superlattices in nanopockets within cobaltite thin films. Nano Lett 11(3), 973–976.Google Scholar
Gulsoy, E.B., Simmons, J.P. & De Graef, M. (2009). Application of joint histogram and mutual information to registration and data fusion problems in serial sectioning microstructure studies. Scripta Mater 60(6), 381–384.Google Scholar
Hansen, P.C. (2010). Discrete Inverse Problems. Philadelphia, PA, USA: Society for Industrial and Applied Mathematics.CrossRefGoogle Scholar
Haruta, M., Kurashima, K., Nagai, T., Komatsu, H., Shimakawa, Y., Kurata, H. & Kimoto, K. (2012). Visualization of hybridization states with atomic resolution using electron energy loss spectroscopy mapping. Appl Phys Lett 100(16), 163107.CrossRefGoogle Scholar
Haruta, M., Nagai, T., Lugg, N.R., Neish, M.J., Nagao, M., Kurashima, K., Allen, L.J., Mizoguchi, T. & Kimoto, K. (2013). Atomic resolution chemical bond analysis of oxygen in La2CuO4 . J Appl Phys 114(8), 083712.Google Scholar
Kim, S., Oshima, Y., Sawada, H., Kaneyama, T., Kondo, Y., Takeguchi, M., Nakayama, Y., Tanishiro, Y. & Takayanagi, K. (2011). Quantitative annular dark-field STEM images of a silicon crystal using a large-angle convergent electron probe with a 300-kV cold field-emission gun. J Electron Micros 60(2), 109–116.Google Scholar
Kimoto, K., Asaka, T., Nagai, T., Saito, M., Matsui, Y. & Ishizuka, K. (2007). Element-selective imaging of atomic columns in a crystal using STEM and EELS. Nature 450, 702–704.CrossRefGoogle Scholar
Kirkland, E.J. (2010). Advanced Computing in Electron Microscopy, 2nd ed. New York, NY, USA: Springer.Google Scholar
Klenov, D.O. & Zide, J.M.O. (2011). Structure of the InAlAs/InP interface by atomically resolved energy dispersive spectroscopy. Appl Phys Lett 99(14), 141904.Google Scholar
Kohl, H. & Rose, H. (1985). Theory of image formation by inelastic scattered electrons in the electron microscope. Adv Imaging Electron Phys 65, 173–227.Google Scholar
Krause, M.O. (1979). Atomic radiative and radiationless yields for K and L shells. J Phys Chem Ref Data 8(2), 307–327.CrossRefGoogle Scholar
LeBeau, J.M., Findlay, S.D., Allen, L.J. & Stemmer, S. (2008). Quantitative atomic resolution scanning transmission electron microscopy. Phys Rev Lett 100, 206101.Google Scholar
LeBeau, J.M., Findlay, S.D., Allen, L.J. & Stemmer, S. (2010). Position averaged convergent beam electron diffraction: Theory and applications. Ultramicroscopy 110(2), 118–125.Google Scholar
Lugg, N.R., Haruta, M., Neish, M.J., Findlay, S.D., Mizoguchi, T., Kimoto, K. & Allen, L.J. (2012). Removing the effects of elastic and thermal scattering from electron energy-loss spectroscopic data. Appl Phys Lett 101(18), 183112.Google Scholar
Muller, D.A., Fitting Kourkoutis, L., Murfitt, M., Song, J.H., Hwang, H.Y., Silcox, J., Dellby, N. & Krivanek, O.L. (2008). Atomic-scale chemical imaging of composition and bonding by aberration-corrected microscopy. Science 319(5866), 1073–1076.CrossRefGoogle ScholarPubMed
Muller, D.A. & Silcox, J. (1995). Delocalization in inelastic scattering. Ultramicroscopy 59(1–4), 195–213.Google Scholar
Mundy, J.A., Mao, Q., Brooks, C.M., Schlom, D.G. & Muller, D.A. (2012). Atomic-resolution chemical imaging of oxygen local bonding environments by electron energy loss spectroscopy. Appl Phy Lett 101(4), 042907.Google Scholar
Neish, M.J., Lugg, N.R., Findlay, S.D., Haruta, M., Kimoto, K. & Allen, L.J. (2013). Detecting the direction of oxygen bonding in SrTiO3 . Phys Rev B 88, 115120.Google Scholar
Prange, M.P., Oxley, M.P., Varela, M., Pennycook, S.J. & Pantelides, S.T. (2012). Simulation of spatially resolved electron energy loss near-edge structure for scanning transmission electron microscopy. Phys Rev Lett 109, 246101.Google Scholar
Press, W.H., Flannery, B.P., Teukolsky, S.A. & Vetterling, W.T. (1992). Numerical Recipes in Fortran 77: The Art of Scientific Computing, 2nd ed. Cambridge: Cambridge University Press.Google Scholar
Rosenauer, A., Gries, K., Müller, K., Pretorius, A., Schowalter, M., Avramescu, A., Engl, K. & Lutgen, S. (2009). Measurement of specimen thickness and composition in using high-angle annular dark field images. Ultramicroscopy 109(9), 1171–1182.Google Scholar
Tan, H., Turner, S., Yücelen, E., Verbeeck, J. & Van Tendeloo, G. (2011). 2D atomic mapping of oxidation states in transition metal oxides by scanning transmission electron microscopy and electron energy-loss spectroscopy. Phys Rev Lett 107, 107602.Google Scholar
Turner, S., Verbeeck, J., Ramezanipour, F., Greedan, J.E., Van Tendeloo, G. & Botton, G.A. (2012). Atomic resolution coordination mapping in Ca2FeCoO5 brownmillerite by spatially resolved electron energy-loss spectroscopy. Chem Mater 24(10), 1904–1909.Google Scholar
Varela, M., Oxley, M.P., Luo, W., Tao, J., Watanabe, M., Lupini, A.R., Pantelides, S.T. & Pennycook, S.J. (2009). Atomic-resolution imaging of oxidation states in manganites. Phys Rev B 79, 085117.Google Scholar
Verbeeck, J., Béché, A. & Van den Broek, W. (2012). A holographic method to measure the source size broadening in STEM. Ultramicroscopy 120, 35–40.Google Scholar
Watanabe, M. & Williams, D.B. (2006). The quantitative analysis of thin specimens: A review of progress from the Cliff-Lorimer to the new ζ-factor methods. J Microsc 221(2), 89–109.Google Scholar
Witte, C., Findlay, S.D., Oxley, M.P., Rehr, J.J. & Allen, L.J. (2009). Theory of dynamical scattering in near-edge electron energy loss spectroscopy. Phys Rev B 80, 184108.CrossRefGoogle Scholar
Xin, H.L., Zhu, Y. & Muller, D.A. (2012). Determining on-axis crystal thickness with quantitative position-averaged incoherent bright-field signal in an aberration-corrected STEM. Microsc Microanal 18, 720–727.Google Scholar
Zhu, Y., Soukiassian, A., Schlom, D.G., Muller, D.A. & Dwyer, C. (2013). Towards artifact-free atomic-resolution elemental mapping with electron energy-loss spectroscopy. Appl Phys Lett 103(14), 141908.Google Scholar