Image-Spectroscopy: New Developments and Applications

1999 ◽  
Vol 5 (S2) ◽  
pp. 618-619 ◽  
Author(s):  
P.J. Thomas ◽  
P.A. Midgley
Keyword(s):  
Spectroscopic Analysis ◽  
Core Loss ◽  
Compositional Analysis ◽  
Single Scattering ◽  
Electron Spectroscopic Imaging ◽  
Low Loss ◽  
Step Size ◽  
New Developments ◽  
Analysis Techniques ◽  
Image Spectroscopy

The ability of modern TEMs to acquire a series of energy filtered images opens up new possibilities in energy loss compositional analysis. In particular, an electron spectroscopic imaging (ESI) series may be treated as a 2-D array of spectra whose resolution is dictated by the step size of the image series, as illustrated in Fig (a). This allows standard spectroscopic analysis techniques to be used on the extracted ‘image-spectra’, such as the removal of plural scattering by deconvolution. Examples of this are given in Fig (b) and (c), which show how Fourier-log and Fourier-ratio deconvolution can be used to recover the single scattering distribution (SSD) from both the low-loss and core-loss regions from a Cr specimen. A pure elemental sample is ideal for testing the validity of such analysis techniques for quantitative compositional mapping, and more details of this method will be published elsewhere. Further, for many simple metal systems, such as steels and alloys, and for simple semiconductors it is possible to model the plasmon contribution using a simple Drude-Lorentz model.

The Thickness Dependence of Energy Loss Spectra

1982 ◽  
Vol 40 ◽  
pp. 486-487
Author(s):  
M. Sarikaya ◽  
P. Rez
Keyword(s):  
Energy Loss ◽  
Multiple Scattering ◽  
Core Loss ◽  
Single Scattering ◽  
Low Loss ◽  
High Loss ◽  
Loss Analysis ◽  
Scattering Spectrum ◽  
Exact Procedure ◽  
Quantitative Analyses

One factor limiting energy loss analysis is the effect of multiple scattering on core loss edge shapes. Multiple scattering distorts fine structures, leads to incorrect quantitative analyses and even affects analysis of extended fine structure (EXELFS). Two procedures for extracting the single scattering spectrum from a spectrum showing the effects of multiple scattering have been proposed. Johnson and Spence derive the single scattering profile by taking the logarithm of the fourier transformed spectrum. If all scattering angles are accepted by the spectrometer this is an exact procedure. Leapman and Swyt have had some success assuming that multiple scattering imposes low loss structure on the high loss part of the spectrum. It is of interest to know how stable these procedures are with thickness and whether the logarithmic deconvolution can be used in thicker specimens than the method described by Leapman and Swyt.

A Practical Method for Removing Plural Scattering from Core Edges in EELS

1981 ◽  
Vol 39 ◽  
pp. 196-197
Author(s):  
R.D. Leapman ◽  
C.R. Swyt
Keyword(s):  
Core Loss ◽  
Practical Method ◽  
Electron Excitation ◽  
Single Scattering ◽  
Low Loss ◽  
High Loss ◽  
The Core ◽  
Electron Energy Loss ◽  
Electron Excitations ◽  
Electron Energy Loss Spectra

Core edges in electron energy loss spectra are generally complicated by thickness effects involving plural inelastic scattering. The fine structure can be modified and errors can be caused in quantitation based on measured edge intensities. Sometimes plural scattering can confuse even identification of elements. In this paper we describe a practical method for eliminating these difficulties.We derive the single scattering distribution, assuming valence electron excitation is small in the core loss region, a reasonable approximation for edges above 100 or 200 eV and for thicknesses of a few hundred Å. We can then separate the spectrum into a “high loss” region H(E) consisting of core edges (less background) and a “low loss” region L(E) containing the zero loss peak, plasmons and one-electron excitations.

Background Fitting in the Low-Loss Region of Electron Energy Loss Spectra

1990 ◽  
Vol 48 (2) ◽  
pp. 56-57
Author(s):  
C P Scott ◽  
A J Craven ◽  
C J Gilmore ◽  
A W Bowen
Keyword(s):  
Energy Loss ◽  
Multiple Scattering ◽  
Simple Form ◽  
Single Scattering ◽  
Low Loss ◽  
Characteristic Energy ◽  
Normal Method ◽  
Fitting In ◽  
Electron Energy Loss ◽  
Electron Energy Loss Spectra

The normal method of background subtraction in quantitative EELS analysis involves fitting an expression of the form I=AE-r to an energy window preceding the edge of interest; E is energy loss, A and r are fitting parameters. The calculated fit is then extrapolated under the edge, allowing the required signal to be extracted. In the case where the characteristic energy loss is small (E < 100eV), the background does not approximate to this simple form. One cause of this is multiple scattering. Even if the effects of multiple scattering are removed by deconvolution, it is not clear that the background from the recovered single scattering distribution follows this simple form, and, in any case, deconvolution can introduce artefacts.The above difficulties are particularly severe in the case of Al-Li alloys, where the Li K edge at ~52eV overlaps the Al L2,3 edge at ~72eV, and sharp plasmon peaks occur at intervals of ~15eV in the low loss region. An alternative background fitting technique, based on the work of Zanchi et al, has been tested on spectra taken from pure Al films, with a view to extending the analysis to Al-Li alloys.

Quantitative energy-filtered tem imaging of interfaces

1996 ◽  
Vol 54 ◽  
pp. 542-543 ◽  
Author(s):  
J. Bentley ◽  
E. A. Kenik ◽  
K. Siangchaew ◽  
M. Libera
Keyword(s):  
Electron Microscopy ◽  
Transmission Electron Microscopy ◽  
Unit Volume ◽  
Core Loss ◽  
Mean Free Path ◽  
Slit Width ◽  
Elemental Mapping ◽  
Low Loss ◽  
Transmission Electron ◽  
Inelastic Mean Free Path

Quantitative elemental mapping by inner shell core-loss energy-filtered transmission electron microscopy (TEM) with a Gatan Imaging Filter (GIF) interfaced to a Philips CM30 TEM operated with a LaB6 filament at 300 kV has been applied to interfaces in a range of materials. Typically, 15s exposures, slit width Δ = 30 eV, TEM magnifications ∼2000 to 5000×, and probe currents ≥200 nA, were used. Net core-loss maps were produced by AE−r background extrapolation from two pre-edge windows. Zero-loss I0 (Δ ≈ 5 eV) and “total” intensity IT (unfiltered, no slit) images were used to produce maps of t/λ = ln(IT/I0), where λ is the total inelastic mean free path. Core-loss images were corrected for diffraction contrast by normalization with low-loss images recorded with the same slit width, and for changes in thickness by normalization with t/λ, maps. Such corrected images have intensities proportional to the concentration in atoms per unit volume. Jump-ratio images (post-edge divided by pre-edge) were also produced. Spectrum lines across planar interfaces were recorded with TEM illumination by operating the GIF in the spectroscopy mode with an area-selecting slit oriented normal to the energy-dispersion direction. Planar interfaces were oriented normal to the area-selecting slit with a specimen rotation holder.

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.

Giotto Unveiled: New Developments in Imaging and Elemental Analysis Techniques for Cultural Heritage

2018 ◽  
pp. 57-66
Author(s):  
Nicola Ludwig ◽  
Letizia Bonizzoni ◽  
Michele Caccia ◽  
Francesco Cavaliere ◽  
Marco Gargano ◽  
...  
Keyword(s):  
Cultural Heritage ◽  
Elemental Analysis ◽  
New Developments ◽  
Analysis Techniques

scholarly journals The Mathematics of Compositional Analysis

2016 ◽  
Vol 45 (4) ◽  
pp. 57-71 ◽  
Author(s):  
Carles Barcelo-Vidal ◽  
Josep-Antoni Martín-Fernández
Keyword(s):  
Scale Invariance ◽  
Compositional Data ◽  
Quotient Space ◽  
Compositional Analysis ◽  
Space Structure ◽  
Compositional Data Analysis ◽  
New Developments ◽  
Quotient Spaces ◽  
Subcompositional Coherence ◽  
Logratio Transformations

The term compositional data analysis is historically associated to the approach based on the logratio transformations introduced in the eighties. Two main principles of this methodology are scale invariance and subcompositional coherence. New developments and concepts emerged in the last decade revealed the need to clarify the concepts of compositions, compositional sample space and subcomposition. In this work the mathematics of compositional analysis based on equivalence relation is presented. The two principles are essential attributes of the corresponding quotient space. A logarithmic isomorphism between quotient spaces induces a metric space structure for compositions. Using this structure, the statistical analysis of compositions consists of analysing logratio coordinates.

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 .

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