Title
Model-based electron microscopy : from images toward precise numbers for unknown structure parameters
Author
Faculty/Department
Faculty of Applied Economics
Faculty of Sciences. Physics
Publication type
article
Publication
Oxford ,
Subject
Physics
Chemistry
Source (journal)
Micron. - Oxford
Volume/pages
43(2012) :4 , p. 509-515
ISSN
0968-4328
ISI
000301702400003
Carrier
E
Target language
English (eng)
Full text (Publishers DOI)
Affiliation
University of Antwerp
Abstract
Statistical parameter estimation theory is proposed as a method to quantify electron microscopy images. It aims at obtaining precise and accurate values for the unknown structure parameters including, for example, atomic column positions and types. In this theory, observations are purely considered as data planes, from which structure parameters have to be determined using a parametric model describing the images. The method enables us to measure positions of atomic columns with a precision of the order of a few picometers even though the resolution of the electron microscope is one or two orders of magnitude larger. Moreover, small differences in averaged atomic number, which cannot be distinguished visually, can be quantified using high-angle annular dark field scanning transmission electron microscopy images. Finally, it is shown how to optimize the experimental design so as to attain the highest precision. As an example, the optimization of the probe size for nanoparticle radius measurements is considered. It is also shown how to quantitatively balance signal-to-noise ratio and resolution by adjusting the probe size.
E-info
https://repository.uantwerpen.be/docman/iruaauth/53e408/ed61209.pdf
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