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HREM-DIMA

HREM-DIMA

(High Resolution Electron Microscopy Digital Image Matching Analysis)

HREM-DIMA iterative digital image matching analysis

last update: 24.5.2013

  • A significant effort has been invested during the last few decades in developing new methods to allow quantitative analysis of HRTEM images (i.e. determination of the positions of atoms). One approach, which has been extensively used by Mobüs et al. [1] for the study of interfaces [2], is based on iterative digital image matching (IDIM) of various model structures by comparison of the experimental image contrast to that obtained from multi-slice image calculations [3,4].
  • This new software program is based on the same concept as IDIM. So far, most programs which use the IDIM approach and implement the image matching in a fully automated process frequently fail and produce incorrect results. The main reason for the failure of these algorithms is that the fully automated iterative matching process frequently gets trapped in a local optimum instead of locating the true global optimum.
  • The new approach which was implemented in HREM-DIMA combines an interactive matching process, which is done by the user controlling the very intuitive graphical user interface (GUI), and a fully quantitative process of comparison between the experimental and simulated micrographs. Fully quantitative results which can be obtained by this approach, allow to determine very precisely the exact conditions at which the experimental data was acquired and ultimately the positions of the projected atomic columns in the specimen.
  • This software was developed using MATLAB (Mathworks Inc.) and is available as a standalone application for both Windows (tested under windows XP & windows 7) and Linux (tested under Ubuntu 10.10). The simulated micrographs are generated using the EMS software developed by P.A. Stadelmann [3].
  • This software, which is under development, allows to extract quantitative information from single experimental HRTEM micrograp
  • This HRTEM quantitative image matching approach is very useful in the following cases:
    • When only a single image is available (for example when large specimen drift is present).
    • To determine the exact acquisition parameters at which a specific micrograph was acquired (for example when working in negative Cs imaging conditions [5]).

References:

  1. G. Mobüs and M. Rühle, Ultramicroscopy, 56[1-3]: 54-70, 1994.
  2. G. Mobüs, A. Levay, B.J. Inkson, M.J. Hÿtch, A. Trampert and T. Wagner, Zeitschrift Fur Metallkunde, 94[4]: 358-367, 2003.
  3. P.A. Stadelmann, Ultramicroscopy, 21[2]: 131-145, 1987.
  4. C.T. Koch, Diss, Arizona State University, 2002.
  5. M. Lentzen, B. Jahnen, C.L. Jia, A. Thust, K. Tillmann and K. Urban, Ultramicroscopy 92:233–242, 2002.

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