Image-Spectroscopy: Applying EELS Analysis Techniques to EFTEM Series

2000 ◽  
Vol 6 (S2) ◽  
pp. 150-151
Author(s):  
P.J. Thomas
Keyword(s):  
Energy Loss ◽  
Spatial Information ◽  
Core Loss ◽  
Three Dimensional ◽  
Data Set ◽  
Spectrum Imaging ◽  
Image Spectroscopy ◽  
Mapping Techniques ◽  
Electron Energy Loss ◽  
Loss Range

The energy-loss spectrum of transmitted electrons contains a wealth of information regarding the physical, chemical and electronic properties of the medium under analysis. It provides a powerful means for materials characterisation in the TEM by use of electron energy-loss spectroscopy (EELS) or its spatially parallel counterpart, energy-selective imaging (ESI). Essentially, both analyses probe the same core-loss information, recording transmitted intensity / as a function of energy-loss E and spatial position x, y, to yield a three-dimensional data set I(E, x, y). Acquisition of an extended series of energy-selected images across the energy-loss range of interest has been shown to provide useful spectral as well as spatial information, with the resolution of extracted ‘image-spectra’ being determined by the energy interval between acquisitions and the width of the energy-selecting slit, as illustrated in Figure la . This mode of analysis, termed ‘image-spectroscopy’ is directly analogous to spectrum-imaging in the STEM, and offers many advantages over conventional two- or three-window elemental mapping techniques .

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

1997 ◽  
Vol 3 (S2) ◽  
pp. 939-940
Author(s):  
N. Brun ◽  
C. Colliex ◽  
K. Suenaga ◽  
M. Tencé ◽  
N. Bonnet
Keyword(s):  
Energy Loss ◽  
Signal To Noise Ratio ◽  
Energy Channel ◽  
Spectral Changes ◽  
New Methods ◽  
Spatially Resolved ◽  
Efficient Processing ◽  
Spectrum Imaging ◽  
Electron Energy Loss ◽  
Loss Range

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.

Scanning Confocal Electron Energy-Loss Microscopy Using Valence-Loss Signals

2013 ◽  
Vol 19 (4) ◽  
pp. 1036-1049 ◽  
Author(s):  
Huolin L. Xin ◽  
Christian Dwyer ◽  
David A. Muller ◽  
Haimei Zheng ◽  
Peter Ercius
Keyword(s):  
Energy Loss ◽  
Electron Energy ◽  
Electron Tomography ◽  
Semiconductor Industry ◽  
Core Loss ◽  
Three Dimensional ◽  
Chromatic Aberration ◽  
Chemical Information ◽  
Tilt Series ◽  
Electron Energy Loss

AbstractFinding a faster alternative to tilt-series electron tomography is critical for rapidly evolving fields such as the semiconductor industry, where failure analysis could greatly benefit from higher throughput. We present a theoretical and experimental evaluation of scanning confocal electron energy-loss microscopy (SCEELM) using valence-loss signals, which is a promising technique for the reliable reconstruction of materials with sub-10-nm resolution. Such a confocal geometry transfers information from the focused portion of the electron beam and enables rapid three-dimensional (3D) reconstruction by depth sectioning. SCEELM can minimize or eliminate the missing-information cone and the elongation problem that are associated with other depth-sectioning image techniques in a transmission electron microscope. Valence-loss SCEELM data acquisition is an order of magnitude faster and requires little postprocessing compared with tilt-series electron tomography. With postspecimen chromatic aberration (Cc) correction, SCEELM signals can be acquired in parallel in the direction of energy dispersion with the aid of a physical pinhole. This increases the efficiency by 10×–100×, and can provide 3D resolved chemical information for multiple core-loss signals simultaneously.

Quantitative Electron Energy Loss Mapping

1985 ◽  
Vol 43 ◽  
pp. 404-405
Author(s):  
R.D. Leapman ◽  
C.R. Swyt
Keyword(s):  
Energy Loss ◽  
Electron Energy ◽  
Electron Energy Loss Spectroscopy ◽  
Elemental Concentration ◽  
Core Loss ◽  
Elemental Distribution ◽  
Electron Energy Loss

The intensity of a characteristic electron energy loss spectroscopy (EELS) image does not, in general, directly reflect the elemental concentration. In fact, the raw core loss image can give a misleading impression of the elemental distribution. This is because the measured core edge signal depends on the amount of plural scattering which can vary significantly from region to region in a sample. Here, we show how the method for quantifying spectra due to Egerton et al. can be extended to maps.

Energy-filtered imaging of polymer microstructure

1996 ◽  
Vol 54 ◽  
pp. 162-163
Author(s):  
K. Siangchaew ◽  
J. Bentley ◽  
M. Libera
Keyword(s):  
Energy Loss ◽  
Heavy Element ◽  
Spectroscopic Imaging ◽  
Data Set ◽  
Polymer Microstructure ◽  
Entire Energy ◽  
Staining Methods ◽  
Spectrum Imaging ◽  
Resolution Data

Energy-filtered electron-spectroscopic TEM imaging provides a new way to study the microstructure of polymers without heavy-element stains. Since spectroscopic imaging exploits the signal generated directly by the electron-specimen interaction, it can produce richer and higher resolution data than possible with most staining methods. There are basically two ways to collect filtered images (fig. 1). Spectrum imaging uses a focused probe that is digitally rastered across a specimen with an entire energy-loss spectrum collected at each x-y pixel to produce a 3-D data set. Alternatively, filtering schemes such as the Zeiss Omega filter and the Gatan Imaging Filter (GIF) acquire individual 2-D images with electrons of a defined range of energy loss (δE) that typically is 5-20 eV.

In Situ Analysis of Surface Contaminant Desorption during Low-Temperature Silicon Substrate Cleaning using Reflection Electron Energy Loss Spectrometry

1992 ◽  
Vol 259 ◽  
Author(s):  
Selmer S. Wong ◽  
Shouleh Nikzad ◽  
Channing C. Ahn ◽  
Aimee L. Smith ◽  
Harry A. Atwater
Keyword(s):  
Low Temperature ◽  
Energy Loss ◽  
Electron Energy ◽  
Core Loss ◽  
Temperature Dependent ◽  
Electron Energy Loss Spectrometry ◽  
Analysis Technique ◽  
Chemical Analysis Technique ◽  
Electron Energy Loss

ABSTRACTWe have employed reflection electron energy loss spectrometry (REELS), a surface chemical analysis technique, in order to analyze contaminant coverages at the submonolayer level during low-temperature in situ cleaning of hydrogen-terminated Si(100). The chemical composition of the surface was analyzed by measurements of the C K, O K and Si L2,3 core loss intensities at various stages of the cleaning. These results were quantified using SiC(100) and SiO2 as reference standards for C and O coverage. Room temperature REELS core loss intensity analysis after sample insertion reveals carbon at fractional monolayer coverage. We have established the REELS detection limit for carbon coverage to be 5±2% of a monolayer. A study of temperature-dependent hydrocarbon desorption from hydrogen-terminated Si(100) reveals the absence of carbon on the surface at temperatures greater than 200°C. This indicates the feasibility of epitaxial growth following an in situ low-temperature cleaning and also indicates the power of REELS as an in situ technique for assessment of surface cleanliness.

scholarly journals Image Formation Based on Atomic Resolution Core-loss Electron Energy Loss Spectroscopy

2006 ◽  
Vol 12 (S02) ◽  
pp. 1138-1139
Author(s):  
MP Oxley ◽  
K van Benthem ◽  
M Varela ◽  
SD Findlay ◽  
LJ Allen ◽  
...  
Keyword(s):  
Energy Loss ◽  
Electron Energy ◽  
Electron Energy Loss Spectroscopy ◽  
Core Loss ◽  
Image Formation ◽  
Atomic Resolution ◽  
Electron Energy Loss

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

Empirical Identification of Uranium Oxides and Fluorides Using Electron Energy-loss Spectroscopy in the Transmission Electron Microscope

1999 ◽  
Vol 5 (6) ◽  
pp. 437-444 ◽  
Author(s):  
Stephen B. Rice ◽  
Hazel H. Bales ◽  
John R. Roth ◽  
Allen L. Whiteside
Keyword(s):  
Energy Loss ◽  
Electron Energy ◽  
Electron Energy Loss Spectroscopy ◽  
Contaminated Soils ◽  
Core Loss ◽  
Uranium Oxides ◽  
Low Loss ◽  
Electron Dose ◽  
Core Losses ◽  
Electron Energy Loss

Abstract: A set of uranium compound particles relevant to contaminated soils and other environmental concerns surrounding uranium bioavailability were studied by electron energy-loss spectroscopy (EELS). Core-loss EELS results suggest that uranium 4+ compounds have an energy loss resolvable from 6+ compounds. Shoulders on the uranium O4,5 edge further distinguish UO2 from UF4. Low-loss characteristics distinguish carbon-free uranium oxide specimens on holey substrates. In the presence of carbon, correction techniques must be applied. Uranium oxides, fluorides, and minerals show a tendency toward reduction of uranium toward 4+ under the beam. The electron dose required to achieve the transformation from 6+ to 4+ is more severe than that usually required to obtain satisfactory spectra, but the possibility for reduction should be considered. The conditions for low-loss analysis need not be as vigorous as those for core losses, and can be done without altering the valence of most oxides.

The Effect of Local Symmetry on Atomic Resolution EELS Near-Edge Structures: Predictions for Grain Boundaries In NiAl

2000 ◽  
Vol 6 (S2) ◽  
pp. 186-187
Author(s):  
D. A. Pankhurst ◽  
G. A. Botton ◽  
C. J. Humphreys
Keyword(s):  
Energy Loss ◽  
Electron Energy ◽  
Local Density ◽  
Spherical Aberration ◽  
Core Loss ◽  
Atomic Scale ◽  
Atomic Resolution ◽  
Atomic Column ◽  
Edge Structure ◽  
Electron Energy Loss

It has been demonstrated that electron energy loss spectrometry (EELS) can be used to probe the electronic structure of materials on the near-atomic scale. The electron energy loss near edge structure (ELNES) observed after the onset of a core edge reflects a weighted local density of final states to which core electrons are excited by fast incident electrons. Lately ‘atomic resolution EELS’ and ‘column-by-column spectroscopy’ have become familiar themes amongst the EELS community. The next generation of STEMs, equipped with spherical aberration (Cs) correctors and electron beam monochromators, will have sufficient spatial and energy resolution, along with the superior signal to noise required, to detect small changes in the ELNES from atomic column to atomic column.Core loss ELNES provides information about unoccupied states, but the structure observed in spectra is sensitive to changes in the underlying occupied states, and thus to the bonding in the material.

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