Improving the Analtical Accuracy in the Analysis of Particles by Employing Low Voltage Analysis:

2000 ◽  
Vol 6 (S2) ◽  
pp. 924-925
Author(s):  
JA Small ◽  
JT Armstrong
Keyword(s):  
Electron Beam ◽  
Electron Probe ◽  
Low Voltage ◽  
X Rays ◽  
Relative Uncertainty ◽  
Particle Volume ◽  
X Ray ◽  
Uncertainty Estimates ◽  
Corrected Data ◽  
Particle Geometry

The energy of the electron beam, in conventional electron probe microanalysis, is generally in the range of 15-25 keV which provides the necessary overvoltage to excite efficiently the K and L x-ray lines for elements with atomic numbers in the range of about 5-83. One of the primary microanalytical methods for obtaining compositional information on particles is X-ray analysis in the electron probe and these same voltage criteria have been applied to the procedures developed for this purpose. The main difference in analytical procedures for bulk samples and particles is that corrections have to be applied to the particle k-ratios or calculated compositions to compensate for: 1) the penetration or scattering of electrons out of the particle volume and 2) variations in the absorption due to particle geometry of x-rays less than about 3 keV. In general, particle corrections improve the accuracy and reduce the relative uncertainty estimates from several tens of percent for uncorrected data to about 10% for corrected data.

Low-Voltage Electron-Probe Microanalysis of Fe–Si Compounds Using Soft X-Rays

2013 ◽  
Vol 19 (6) ◽  
pp. 1698-1708 ◽  
Author(s):  
Phillip Gopon ◽  
John Fournelle ◽  
Peter E. Sobol ◽  
Xavier Llovet
Keyword(s):  
Electron Probe Microanalysis ◽  
Electron Probe ◽  
Low Voltage ◽  
Mass Attenuation Coefficient ◽  
X Rays ◽  
X Ray ◽  
Voltage Electron ◽  
Increased Sensitivity ◽  
Quantitative Analyses ◽  
Areas Of Interest

AbstractConventional electron-probe microanalysis has an X-ray analytical spatial resolution on the order of 1–4 μm width/depth. Many of the naturally occurring Fe–Si compounds analyzed in this study are smaller than 1 μm in size, requiring the use of lower accelerating potentials and nonstandard X-ray lines for analysis. Problems with the use of low-energy X-ray lines (soft X-rays) of iron for quantitative analyses are discussed and a review is given of the alternative X-ray lines that may be used for iron at or below 5 keV (i.e., accelerating voltage that allows analysis of areas of interest <1 μm). Problems include increased sensitivity to surface effects for soft X-rays, peak shifts (induced by chemical bonding, differential self-absorption, and/or buildup of carbon contamination), uncertainties in the mass attenuation coefficient for X-ray lines near absorption edges, and issues with spectral resolution and count rates from the available Bragg diffractors. In addition to the results from the traditionally used Fe Lα line, alternative approaches, utilizing Fe Lβ, and Fe Ll-η lines, are discussed.

Characteristic and Continuum Fluorescence in Electron Beam X-ray Microanalysis

1999 ◽  
Vol 5 (S2) ◽  
pp. 562-563
Author(s):  
C.E. Nockolds
Keyword(s):  
Electron Beam ◽  
Electron Probe Microanalysis ◽  
Electron Probe ◽  
Mathematical Framework ◽  
X Rays ◽  
Correction Procedure ◽  
X Ray ◽  
Exponential Term ◽  
Accurate Expression ◽  
Original Formula

Of the different aspects of electron probe microanalysis(EPMA)which were studied by Castaing during his doctorate the work on characteristic x-ray fluorescence was the most definitive. In his thesis, which was completed in 1951, Castaing established the physical and mathematical framework for a correction procedure for fluorescence which is essentially still used in EPMA today. Much of the effort since then has been in refining and improving the accuracy of the correction and extending the scope of the correction to a wider range of specimen types. The Castaing formula was developed for the case of a K x-ray from element A being excited by a K xray from element B (K-K fluorescence) and in 1965 Reed extended the range of the correction by including the K-L, L-L and L-K interactions. In the same paper Reed also introduced the expression from Green and Cosslett for the calculation of K intensities, which was believed to be more accurate than the expression used by Castaing. The original formula included a somewhat unrealistic exponential term to allow for the depth of the production of the primary x-rays and a number of workers have tried replacing this term with a more accurate expression, however, in general this has led to only small changes in the final correction. Reed also simplified the formula in order to make the calculation easier in the days before fast computers; in particular he replaced the jump ratio variable by two constants, one for the K-shell and one for the L-shell. Much later Heinrich showed that this simplification was no longer necessary and that the jump ratio could in fact be calculated directly.

The measurement of the fluorescence of Si K x-rays by Au M x-rays

1990 ◽  
Vol 48 (2) ◽  
pp. 198-199
Author(s):  
John A. Small ◽  
Scott A. Wight ◽  
Robert L. Myklebust ◽  
Dale E. Newbury
Keyword(s):  
Electron Beam ◽  
Electron Probe ◽  
Primary Electron ◽  
Characteristic Line ◽  
X Rays ◽  
Limited Information ◽  
Primary Electron Beam ◽  
X Ray ◽  
Image Position ◽  
Critical Excitation

The characteristic fluorescence correction is used in electron probe microanalysis to account for the x-ray intensity excited in element “a” by the x-rays from the characteristic line of another element, “b”, in the sample. Since the excited intensity is not generated by the primary electron beam, it is necessary to apply the fluorescence correction for quantitative elemental analysis. This correction can be significant particularly when element “b” is a major component of the sample and the characteristic line for element “b” is slightly higher in energy than the critical excitation energy for the excited line of element “a”.The fluorescence correction, which is used in the various analytical programs, is described in equation 1.where I'*fa/I'*pa is the ratio of the emitted “a” intensity excited by “b” x-rays to the emitted intensity excited by the primary electron beam. The various parameters in this equation are accurately known for the K x-ray lines, but only very limited information is available for the M x-ray lines.

Using DTSA-II to Simulate and Interpret Energy Dispersive Spectra from Particles

2010 ◽  
Vol 16 (3) ◽  
pp. 248-258 ◽  
Author(s):  
Nicholas W.M. Ritchie
Keyword(s):  
Electron Beam ◽  
Copper Substrate ◽  
Lateral Spread ◽  
Angle Of Incidence ◽  
X Rays ◽  
Scattered Electron ◽  
Particle Volume ◽  
X Ray ◽  
Sample Configuration ◽  
Naive Model

AbstractA high quality X-ray spectrum image of a 3.3 μm diameter sphere of K411 glass resting on a copper substrate was collected at 25 keV. The same sample configuration was modeled using the NISTMonte Monte Carlo simulation of electron and X-ray transport as is integrated into the quantitative X-ray microanalysis software package DTSA-II. The distribution of measured and simulated X-ray intensity compare favorably for all the major lines present in the spectra. The simulation is further examined to investigate the influence of angle-of-incidence, sample thickness, and sample diameter on the generated and measured X-ray intensity. The distribution of generated X-rays is seen to deviate significantly from a naive model which assumes that the distribution of generated X-rays is similar to bulk within the volume they share in common. It is demonstrated that the angle at which the electron beam strikes the sample has nonnegligible consequences. It is also demonstrated that within the volume that the bulk and particle share in common that electrons, which have exited and later reentered the particle volume, generate a significant fraction of the X-rays. Any general model of X-ray generation in particles must take into account the lateral spread of the scattered electron beam.

X-ray micro tomography in the scanning electron microscope

1978 ◽  
Vol 36 (1) ◽  
pp. 106-107 ◽  
Author(s):  
W. Brünger
Keyword(s):  
Electron Beam ◽  
Electron Microscope ◽  
Scanning Electron Microscope ◽  
Target Surface ◽  
The Body ◽  
X Rays ◽  
Cross Sectional ◽  
X Ray ◽  
Micro Tomography ◽  
Scanning Electron

Reconstructive tomography is a new technique in diagnostic radiology for imaging cross-sectional planes of the human body /1/. A collimated beam of X-rays is scanned through a thin slice of the body and the transmitted intensity is recorded by a detector giving a linear shadow graph or projection (see fig. 1). Many of these projections at different angles are used to reconstruct the body-layer, usually with the aid of a computer. The picture element size of present tomographic scanners is approximately 1.1 mm2.Micro tomography can be realized using the very fine X-ray source generated by the focused electron beam of a scanning electron microscope (see fig. 2). The translation of the X-ray source is done by a line scan of the electron beam on a polished target surface /2/. Projections at different angles are produced by rotating the object.During the registration of a single scan the electron beam is deflected in one direction only, while both deflections are operating in the display tube.

High spatial resolution x-ray microanalysis of interfaces

1995 ◽  
Vol 53 ◽  
pp. 284-285
Author(s):  
J. R. Michael
Keyword(s):  
Spatial Resolution ◽  
Electron Probe ◽  
Solid Angle ◽  
Collection Efficiency ◽  
Spatial Scales ◽  
Energy Dispersive Spectrometer ◽  
X Rays ◽  
X Ray ◽  
Probe Size ◽  
Brightness Field

X-ray microanalysis in the analytical electron microscope (AEM) refers to a technique by which chemical composition can be determined on spatial scales of less than 10 nm. There are many factors that influence the quality of x-ray microanalysis. The minimum probe size with sufficient current for microanalysis that can be generated determines the ultimate spatial resolution of each individual microanalysis. However, it is also necessary to collect efficiently the x-rays generated. Modern high brightness field emission gun equipped AEMs can now generate probes that are less than 1 nm in diameter with high probe currents. Improving the x-ray collection solid angle of the solid state energy dispersive spectrometer (EDS) results in more efficient collection of x-ray generated by the interaction of the electron probe with the specimen, thus reducing the minimum detectability limit. The combination of decreased interaction volume due to smaller electron probe size and the increased collection efficiency due to larger solid angle of x-ray collection should enhance our ability to study interfacial segregation.

scholarly journals Search for intermittent X-ray pulsations from neutron stars in low-mass X-ray binaries

2021 ◽  
Vol 38 ◽  
Author(s):  
Yunus Emre Bahar ◽  
Manoneeta Chakraborty ◽  
Ersin Göğüş
Keyword(s):  
Neutron Stars ◽  
Orbital Period ◽  
Oscillation Frequency ◽  
Orbital Motion ◽  
X Rays ◽  
X Ray ◽  
Second Stage ◽  
Corrected Data ◽  
Low Mass ◽  
X Ray Binaries

Abstract We present the results of our extensive binary orbital motion corrected pulsation search for 13 low-mass X-ray binaries. These selected sources exhibit burst oscillations in X-rays with frequencies ranging from 45 to 1 122 Hz and have a binary orbital period varying from 2.1 to 18.9 h. We first determined episodes that contain weak pulsations around the burst oscillation frequency by searching all archival Rossi X-ray Timing Explorer data of these sources. Then, we applied Doppler corrections to these pulsation episodes to discard the smearing effect of the binary orbital motion and searched for recovered pulsations at the second stage. Here we report 75 pulsation episodes that contain weak but coherent pulsations around the burst oscillation frequency. Furthermore, we report eight new episodes that show relatively strong pulsations in the binary orbital motion corrected data.

Uncertainty Estimates for Electron Probe X-ray Microanalysis Measurements

2012 ◽  
Vol 84 (22) ◽  
pp. 9956-9962 ◽  
Author(s):  
Nicholas W. M. Ritchie ◽  
Dale E. Newbury
Keyword(s):  
Electron Probe ◽  
X Ray ◽  
Uncertainty Estimates

Some of these could also be operated in the energy range above lOMeV for experiments designed to determine at which energy level radioactivity can be induced in the irradiated medium. A linac with a maximum energy of 25 MeV was commissioned for the U.S. Army Natick Research and Development Labora­ tories in 1963. Its beam power was 6.5 kW at an electron energy of 10 MeV, 18 kW at 24 MeV. Assuming 100% efficiency, a 1-kW beam can irradiate 360 kg of product with a dose of 10 kGy/h. The efficiency of electron accelerators is higher than that of gamma sources because the electron beam can be directed at the product, whereas the gamma sources emit radiation in all directions. An efficiency of 50% is a realistic assumption for accelerator facilities. With that and 6.5 kW beam power an accelerator of the type built for the Natick laboratories can process about 1.2t/h at 10 kGy. In Odessa in the former Soviet Union, now in the Ukraine, two 20-kW accelerators with an energy of 1.4 MeV installed next to a grain elevator went into operation in 1983. Each accelerator has the capacity to irradiate 200 t of wheat per hour with a dose of 200 Gy for insect disinfestation. This corresponds to a beam utilization of 56% (9). In France, a facility for electron irradiation of frozen deboned chicken meat commenced operation at Berric near Vannes (Brittany) in late 1986. The purpose of irradiation is to improve the hygienic quality of the meat by destroying salmonella and other disease-causing (pathogenic) microorganisms. The electron beam accelerator is a 7 MeV/10 kW Cassitron built by CGR-MeV (10). An irradiation facility of this type is shown in Figure . Because of their relatively low depth of penetration electron beams cannot be used for the irradiation of animal carcasses, large packages, or other thick materials. However, this difficulty can be overcome by converting the electrons to x-rays. As indicated in Figure 9, this can be done by fitting a water-cooled metal plate to the scanner. Whereas in conventional x-ray tubes the conversion of electron energy to x-ray energy occurs only with an efficiency of about %, much higher efficiencies can be achieved in electron accelerators. The conversion efficiency depends on the material of the converter plate (target) and on the electron energy. Copper converts 5-MeV electrons with about 7% efficiency, 10-MeV electrons with 12% efficiency. A tungsten target can convert 5-MeV electrons with about 20%, 10-MeV electrons with 30% efficiency. (Exact values depend on target thickness.) In contrast to the distinct gamma radiation energy emitted from radionuclides and to the monoenergetic electrons produced by accelerators, the energy spectrum of x-rays is continuous from the value equivalent to the energy of the bombarding electrons to zero. The intensity of this spectrum peaks at about one-tenth of the maximum energy value. The exact location of the intensity peak depends on the thickness of the converter plate and on some other factors. As indicated in Figure

1995 ◽  
pp. 40-40
Keyword(s):  
Electron Beam ◽  
Electron Energy ◽  
Maximum Energy ◽  
Metal Plate ◽  
Beam Power ◽  
X Rays ◽  
X Ray ◽  
Emit Radiation ◽  
Electron Accelerators ◽  
Gamma Sources

scholarly journals Objective Evaluation of Deep Uncertainty Predictions for COVID-19 Detection

2021 ◽  
Author(s):  
Hamzeh Asgharnezhad ◽  
Afshar Shamsi ◽  
Roohallah Alizadehsani ◽  
Abbas Khosravi ◽  
Saeid Nahavandi ◽  
...  
Keyword(s):  
Uncertainty Quantification ◽  
Performance Metrics ◽  
Confusion Matrix ◽  
Objective Evaluation ◽  
X Rays ◽  
The Novel ◽  
X Ray ◽  
Uncertainty Estimates ◽  
Chest X Ray ◽  
Novel Concept

Abstract Deep neural networks (DNNs) have been widely applied for detecting COVID-19 in medical images. Existing studies mainly apply transfer learning and other data representation strategies to generate accurate point estimates. The generalization power of these networks is always questionable due to being developed using small datasets and failing to report their predictive confidence. Quantifying uncertainties associated with DNN predictions is a prerequisite for their trusted deployment in medical settings. Here we apply and evaluate three uncertainty quantification techniques for COVID-19 detection using chest X-Ray (CXR) images. The novel concept of uncertainty confusion matrix is proposed and new performance metrics for the objective evaluation of uncertainty estimates are introduced. Through comprehensive experiments, it is shown that networks pertained on CXR images outperform networks pretrained on natural image datasets such as ImageNet. Qualitatively and quantitatively evaluations also reveal that the predictive uncertainty estimates are statistically higher for erroneous predictions than correct predictions. Accordingly, uncertainty quantification methods are capable of flagging risky predictions with high uncertainty estimates. We also observe that ensemble methods more reliably capture uncertainties during the inference. DNN-based solutions for COVID-19 detection have been mainly proposed without any principled mechanism for risk mitigation. Previous studies have mainly focused on on generating single-valued predictions using pretrained DNNs. In this paper, we comprehensively apply and comparatively evaluate three uncertainty quantification techniques for COVID-19 detection using chest X-Ray images. The novel concept of uncertainty confusion matrix is proposed and new performance metrics for the objective evaluation of uncertainty estimates are introduced for the first time. Using these new uncertainty performance metrics, we quantitatively demonstrate where and when we could trust DNN predictions for COVID-19 detection from chest X-rays. It is important to note the proposed novel uncertainty evaluation metrics are generic and could be applied for evaluation of probabilistic forecasts in all classification problems.

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