Journal
ULTRAMICROSCOPY
Volume 137, Issue -, Pages 12-19Publisher
ELSEVIER
DOI: 10.1016/j.ultramic.2013.11.001
Keywords
HAADF STEM; Composition determination; Statistical parameter estimation theory; STEM simulations
Categories
Funding
- Research Foundation Flanders (FWO, Belgium) [G.0393.11, G.0064.10, G.0374.13, G.0184.09, G.0044.13]
- Ph.D. research grant
- European Research Council [246791 - COUNTATOMS]
- DFG [RO2057/8-1]
- European Union [312483 (ESTEEM2)]
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High angle annular dark field scanning transmission electron microscopy (HAADF STEM) images provide sample information which is sensitive to the chemical composition. The image intensities indeed scale with the mean atomic number Z. To some extent, chemically different atomic column types can therefore be visually distinguished. However, in order to quantity the atomic column composition with high accuracy and precision, model-based methods are necessary. Therefore, an empirical incoherent parametric imaging model can be used of which the unknown parameters are determined using statistical parameter estimation theory (Van Aert et al., 2009, [1]). In this paper, it will be shown how this method can be combined with frozen lattice multislice simulations in order to evolve from a relative toward an absolute quantification of the composition of single atomic columns with mixed atom types. Furthermore, the validity of the model assumptions are explored and ;discussed. (C) 2013 Elsevier B.V. All rights reserved
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