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The Importance of Averaging to Interpret Electron Correlographs of Disordered Materials

Published online by Cambridge University Press:  19 February 2014

Tao Sun*
Affiliation:
Advanced Photon Source, Argonne National Laboratory, Argonne, IL 60439, USA
Michael M.J. Treacy
Affiliation:
Department of Physics, Arizona State University, Tempe, AZ 85287, USA
Tian Li
Affiliation:
Department of Materials Science and Engineering, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA
Nestor J. Zaluzec
Affiliation:
Electron Microscopy Center, Argonne National Laboratory, Argonne, IL 60439, USA
J. Murray Gibson*
Affiliation:
Department of Physics, Northeastern University, Boston, MA 02115, USA
*
*Corresponding author. taosun@aps.anl.gov; m.gibson@neu.edu
*Corresponding author. taosun@aps.anl.gov; m.gibson@neu.edu
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Abstract

The development of effective new tools for structural characterization of disordered materials and systems is becoming increasingly important as such tools provide the key to understanding, and ultimately controlling, their properties. The relatively novel technique of correlograph analysis (i.e., the approach of calculating angular autocorrelations within diffraction patterns) promises unique advantages for probing the local symmetries of disordered structures. Because correlograph analysis examines a component of the high-order four-body correlation function, it is more sensitive to medium-range ordering than conventional diffraction methods. As a follow-up of our previous publication, where we studied thin samples of sputtered amorphous silicon, we describe here the practical experimental method and common systematic errors of electron correlograph analysis. Using both experimental data and numerical simulations, we demonstrate that reliable structural information about the sample can only be extracted from the mean correlograph averaged over a sufficient number of individual results.

Type
Materials Applications
Copyright
© Microscopy Society of America 2014 

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