Quantitative determination of iron oxidation states in minerals using Fe L 2,3 -edge electron energy-loss near-edge structure spectroscopy

1998 ◽  
Vol 25 (5) ◽  
pp. 323-327 ◽  
Author(s):  
P. A. van Aken ◽  
B. Liebscher ◽  
V. J. Styrsa
Keyword(s):  
Energy Loss ◽  
Quantitative Determination ◽  
Electron Energy ◽  
Iron Oxidation ◽  
Oxidation States ◽  
Edge Structure ◽  
Electron Energy Loss ◽  
Iron Oxidation States

The determination of Ti, Mn and Fe oxidation states in minerals by electron energy-loss spectroscopy

1985 ◽  
Vol 18 (1-4) ◽  
pp. 285-289 ◽  
Author(s):  
Max T. Otten ◽  
Barbara Miner ◽  
James H. Rask ◽  
Peter R. Buseck
Keyword(s):  
Energy Loss ◽  
Electron Energy ◽  
Electron Energy Loss Spectroscopy ◽  
Oxidation States ◽  
Fe Oxidation ◽  
Electron Energy Loss

Auger and EELS Study of a-Si1−x Cx:H Alloys

1991 ◽  
Vol 219 ◽  
Author(s):  
M.De Seta ◽  
P. Narducci ◽  
F. Evangelisti
Keyword(s):  
Simple Model ◽  
Energy Loss ◽  
Quantitative Determination ◽  
Electron Energy ◽  
Local Bonding ◽  
Auger Spectra ◽  
Low X ◽  
Electron Energy Loss

ABSTRACTIt is shown that Auger and electron energy loss spectroscopies can provide a well defined picture of the local bonding and structure of a-Si1−x Cx:H alloys. The samples were found macroscopically homogeneous but microscopically heterogeneous on a scale of few Angstroms. A simple model where the tetrahedral network is chemically ordered at low x values and carbon tends to segregate in C-C microclusters at high x values seems to reproduce the data very well. By fitting the C and Si Auger spectra it was possible to have a quantitative determination of the percentage of different configurations.

Electron energy-loss near-edge structure in silicate minerals

1992 ◽  
Vol 50 (2) ◽  
pp. 1258-1259
Author(s):  
D W McComb ◽  
R S Payne ◽  
P L Hansen ◽  
R Brydson
Keyword(s):  
Solid State ◽  
Energy Loss ◽  
Electron Energy ◽  
State Energy ◽  
Local Environment ◽  
Edge Structure ◽  
Silicate Minerals ◽  
Two Samples ◽  
Electron Energy Loss ◽  
Careful Processing

Electron energy-loss near-edge structure (ELNES) is an effective probe of the local geometrical and electronic environment around particular atomic species in the solid state. Energy-loss spectra from several silicate minerals were mostly acquired using a VG HB501 STEM fitted with a parallel detector. Typically a collection angle of ≈8mrad was used, and an energy resolution of ≈0.5eV was achieved.Other authors have indicated that the ELNES of the Si L2,3-edge in α-quartz is dominated by the local environment of the silicon atom i.e. the SiO4 tetrahedron. On this basis, and from results on other minerals, the concept of a coordination fingerprint for certain atoms in minerals has been proposed. The concept is useful in some cases, illustrated here using results from a study of the Al2SiO5 polymorphs (Fig.l). The Al L2,3-edge of kyanite, which contains only 6-coordinate Al, is easily distinguished from andalusite (5- & 6-coordinate Al) and sillimanite (4- & 6-coordinate Al). At the Al K-edge even the latter two samples exhibit differences; with careful processing, the fingerprint for 4-, 5- and 6-coordinate aluminium may be obtained.

Combined ab-initio and N-K, Ti-L2,3, V-L2,3 electron energy-loss near edge structure studies for TiN and VN films

2007 ◽  
Vol 98 (11) ◽  
pp. 1060-1065 ◽  
Author(s):  
Boriana Rashkova ◽  
Petr Lazar ◽  
Josef Redinger ◽  
Raimund Podloucky ◽  
Gerald Kothleitner ◽  
...  
Keyword(s):  
Energy Loss ◽  
Ab Initio ◽  
Electron Energy ◽  
Edge Structure ◽  
Electron Energy Loss

The Use of ELNES for Microanalysis

1999 ◽  
Vol 5 (S2) ◽  
pp. 664-665
Author(s):  
A.J. Craven ◽  
M. MacKenzie
Keyword(s):  
Electron Microscopy ◽  
Energy Loss ◽  
Electron Energy ◽  
Analytical Electron Microscopy ◽  
Local Environment ◽  
Edge Structure ◽  
Similar Shape ◽  
Analytical Electron ◽  
Electron Energy Loss ◽  
Combining Information

The performance of many materials systems depends on our ability to control the distribution of atoms on a nanometre or sub-nanometre scale within those systems. This is as true for steels as it is for semiconductors. A key requirement for improving their performance is the ability to determine the distribution of the elements resulting from processing the material under a given set of conditions. Analytical electron microscopy (AEM) provides a range of powerful techniques with which to investigate this distribution. By combining information from different techniques, many of the ambiguities of interpretation of the data from an individual technique can be eliminated. The electron energy loss near edge structure (ELNES) present on an ionisation edge in the electron energy loss spectrum reflects the local structural and chemical environments in which the particular atomic species occurs. Thus it is a useful contribution to the information available. Since a similar local environment frequently results in a similar shape, ELNES is useful as a “fingerprint”.

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