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Recording, Processing and Extracting Information From Sequences of Spatially Resolved Eels Spectra

Published online by Cambridge University Press:  02 July 2020

N. Brun
Affiliation:
Laboratoire de Physique des Solides, CNRS URA 002, Bât. 510, Université Paris Sud, 91405, Orsay, France
C. Colliex
Affiliation:
Laboratoire de Physique des Solides, CNRS URA 002, Bât. 510, Université Paris Sud, 91405, Orsay, France Laboratoire Aimé Cotton, CNRS UPR 3321, Bât. 505, Université Paris Sud, 91405, Orsay, France
K. Suenaga
Affiliation:
Laboratoire de Physique des Solides, CNRS URA 002, Bât. 510, Université Paris Sud, 91405, Orsay, France
M. Tencé
Affiliation:
Laboratoire de Physique des Solides, CNRS URA 002, Bât. 510, Université Paris Sud, 91405, Orsay, France
N. Bonnet
Affiliation:
Unité INSERM 314, 21 rue Clément Ader, 51685, Reims, Cedex 2, France
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Extract

The sophisticated acquisition procedures now available in time or space resolved spectroscopies, also known as spectrum-imaging modes, produce large amounts of data which require specific developments for efficient processing and information extraction. For instance, in electron energy-loss spectroscopy (EELS), a line-spectrum consists of typically one hundred spectra recorded at regular intervals when scanning the subnanometer incident electron probe across the feature of interest: interfaces, multilayers or nanostructures of various shapes and dimensions. The useful information in any of these spectra depends on many factors such as the problem under investigation, the involved energy-loss range or the signal-to-noise ratio of the different features. However it is generally contained in the spectral changes, as well in energy channel as in position along the sequence.

To detect, measure and identify these variations, new methods have to be developed and the accompanying algorithms to be implemented. A first category encompasses all the routines which apply successively to all spectra in the sequence the well-known software which have been elaborated for processing individual spectra.

Type
Quantitative Analysis For Series of Spectra and Images: Getting The Most From Your Experimental Data
Copyright
Copyright © Microscopy Society of America 1997

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References

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