scholarly journals Signatures of distinct impurity configurations in atomic-resolution valence electron-energy-loss spectroscopy: Application to graphene

2016 ◽  
Vol 94 (15) ◽  
Author(s):  
Myron D. Kapetanakis ◽  
Mark P. Oxley ◽  
Wu Zhou ◽  
Stephen J. Pennycook ◽  
Juan-Carlos Idrobo ◽  
...  
Author(s):  
N. D. Browning ◽  
M. M. McGibbon ◽  
M. F. Chisholm ◽  
S. J. Pennycook

The recent development of the Z-contrast imaging technique for the VG HB501 UX dedicated STEM, has added a high-resolution imaging facility to a microscope used mainly for microanalysis. This imaging technique not only provides a high-resolution reference image, but as it can be performed simultaneously with electron energy loss spectroscopy (EELS), can be used to position the electron probe at the atomic scale. The spatial resolution of both the image and the energy loss spectrum can be identical, and in principle limited only by the 2.2 Å probe size of the microscope. There now exists, therefore, the possibility to perform chemical analysis of materials on the scale of single atomic columns or planes.In order to achieve atomic resolution energy loss spectroscopy, the range over which a fast electron can cause a particular excitation event, must be less than the interatomic spacing. This range is described classically by the impact parameter, b, which ranges from ~10 Å for the low loss region of the spectrum to <1Å for the core losses.


2012 ◽  
Vol 18 (4) ◽  
pp. 667-675 ◽  
Author(s):  
Paul Cueva ◽  
Robert Hovden ◽  
Julia A. Mundy ◽  
Huolin L. Xin ◽  
David A. Muller

AbstractThe high beam current and subangstrom resolution of aberration-corrected scanning transmission electron microscopes has enabled electron energy loss spectroscopy (EELS) mapping with atomic resolution. These spectral maps are often dose limited and spatially oversampled, leading to low counts/channel and are thus highly sensitive to errors in background estimation. However, by taking advantage of redundancy in the dataset map, one can improve background estimation and increase chemical sensitivity. We consider two such approaches—linear combination of power laws and local background averaging—that reduce background error and improve signal extraction. Principal component analysis (PCA) can also be used to analyze spectrum images, but the poor peak-to-background ratio in EELS can lead to serious artifacts if raw EELS data are PCA filtered. We identify common artifacts and discuss alternative approaches. These algorithms are implemented within the Cornell Spectrum Imager, an open source software package for spectroscopic analysis.


2006 ◽  
Vol 12 (S02) ◽  
pp. 1138-1139
Author(s):  
MP Oxley ◽  
K van Benthem ◽  
M Varela ◽  
SD Findlay ◽  
LJ Allen ◽  
...  

Extended abstract of a paper presented at Microscopy and Microanalysis 2006 in Chicago, Illinois, USA, July 30 – August 3, 2006


2013 ◽  
Vol 124 ◽  
pp. 130-138 ◽  
Author(s):  
Jeffery A. Aguiar ◽  
Bryan W. Reed ◽  
Quentin M. Ramasse ◽  
Rolf Erni ◽  
Nigel D. Browning

2014 ◽  
Vol 115 (3) ◽  
pp. 034302 ◽  
Author(s):  
J. Palisaitis ◽  
A. Lundskog ◽  
U. Forsberg ◽  
E. Janzén ◽  
J. Birch ◽  
...  

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