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Real-time EELS spectra classification using Principal Components Analysis (PCA) and Artificial Neural Networks (ANN)

Published online by Cambridge University Press:  02 July 2020

P-G Åstrand  and
S. Csillag
P-G Åstrand
Affiliation:
Department of Physics, Stockholm University, Box 6730, S-113 85 Stockholm, Sweden
S. Csillag
Affiliation:
Department of Physics, Stockholm University, Box 6730, S-113 85 Stockholm, Sweden
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Abstract

Recent developments in detector technology [1] for EELS and Energy Filtered TEM has made possible to obtain large number of spectra and energy filtered images during very short exposure times. This in turn opens the exciting possibility of studying time dependent processes in the electron microscope, during exposure to the electron beam as well as the study of different radiation sensitive samples which are being degraded during lengthily data recording. This kind of data recording generates a large amount of data and manual data analysis should be avoided in order to be able to fully benefit from the improved sensitivity and increased speed of these new detectors. Thus a fast, real-time data analysis system is highly desirable.

A system for real-time data analysis (spectra classification) of data generated from such a detector has been simulated in a program based on the object oriented C++ framework ROOT [2][3].

Type
EELS Microanalysis at High Sensitivity: Advances in Spectrum Imaging, Energy Filtering and Detection (Organized by R. Leapman and J. Bruley)
Information
Microscopy and Microanalysis , Volume 7 , Issue S2: Proceedings: Microscopy & Microanalysis 2001, Microscopy Society of America 59th Annual Meeting, Microbeam Analysis Society 35th Annual Meeting, Long Beach, California August 5-9, 2001 , August 2001 , pp. 1164 - 1165
Copyright
Copyright © Microscopy Society of America 2001

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References

References:

[1]Orsholm, C., Borglund, N., Csillag, S.. High detective quantum efficiency fast electron detector for electron energy loss spectroscopy. Micron31 2000CrossRefGoogle Scholar
[2] See internet: http://root.cern.chGoogle Scholar
[3] See internet: http://svedaq.tsl.uu.se/anton/neural.htmlGoogle Scholar
[4] See internet: http://www.cemes.fr/eelsdb/Google Scholar