Quantitative Analysis of the Photodegradation of Emitting CdTe Nanocrystals Dispersed in Glass Films

2005 ◽  
Vol 109 (38) ◽  
pp. 17855-17860 ◽  
Author(s):  
N. Murase ◽  
P. Yang ◽  
C. L. Li
Keyword(s):  
Quantitative Analysis ◽  
Cdte Nanocrystals ◽  
Glass Films

Quantitative analysis of borophosphosilicate glass films on silicon using infrared external reflection–absorption spectroscopy

1995 ◽  
Vol 13 (4) ◽  
pp. 1959-1966 ◽  
Author(s):  
James E. Franke ◽  
Lizhong Zhang ◽  
Thomas M. Niemczyk ◽  
David M. Haaland ◽  
Kenneth J. Radigan
Keyword(s):  
Quantitative Analysis ◽  
Absorption Spectroscopy ◽  
Borophosphosilicate Glass ◽  
Glass Films

Quantitative Analysis of Infrared Reflection Spectra from Phosphosilicate Glass Films

1993 ◽  
Vol 140 (5) ◽  
pp. 1425-1429 ◽  
Author(s):  
James E. Franke ◽  
Lizhong Zhang ◽  
Thomas M. Niemczyk ◽  
David M. Haaland ◽  
Jack H. Linn
Keyword(s):  
Quantitative Analysis ◽  
Reflection Spectra ◽  
Infrared Reflection ◽  
Phosphosilicate Glass ◽  
Glass Films

An Improved Quantitative Image Analyser

1977 ◽  
Vol 35 ◽  
pp. 226-227
Author(s):  
J.P. Fallon ◽  
P.J. Gregory ◽  
C.J. Taylor
Keyword(s):  
Feature Extraction ◽  
Quantitative Analysis ◽  
Frequency Content ◽  
General Sense ◽  
Physical Measurements ◽  
Quantitative Image ◽  
Image Analyser ◽  
Automatic Methods ◽  
Quantitative Results

Quantitative image analysis systems have been used for several years in research and quality control applications in various fields including metallurgy and medicine. The technique has been applied as an extension of subjective microscopy to problems requiring quantitative results and which are amenable to automatic methods of interpretation.Feature extraction. In the most general sense, a feature can be defined as a portion of the image which differs in some consistent way from the background. A feature may be characterized by the density difference between itself and the background, by an edge gradient, or by the spatial frequency content (texture) within its boundaries. The task of feature extraction includes recognition of features and encoding of the associated information for quantitative analysis.Quantitative Analysis. Quantitative analysis is the determination of one or more physical measurements of each feature. These measurements may be straightforward ones such as area, length, or perimeter, or more complex stereological measurements such as convex perimeter or Feret's diameter.

Quantification of Silica Uptake by Alveolar Macrophages - An Emperical Scanning Electron Microprobe Method

1982 ◽  
Vol 40 ◽  
pp. 332-333
Author(s):  
V. V. Damiano ◽  
R. P. Daniele ◽  
H. T. Tucker ◽  
J. H. Dauber
Keyword(s):  
Quantitative Analysis ◽  
Alveolar Macrophages ◽  
Bulk Sample ◽  
Silica Particles ◽  
Empirical Method ◽  
Phagocytic Cells ◽  
Calibration Standards ◽  
X Ray ◽  
Accurate Quantitative Analysis ◽  
Scanning Electron

An important example of intracellular particles is encountered in silicosis where alveolar macrophages ingest inspired silica particles. The quantitation of the silica uptake by these cells may be a potentially useful method for monitoring silica exposure. Accurate quantitative analysis of ingested silica by phagocytic cells is difficult because the particles are frequently small, irregularly shaped and cannot be visualized within the cells. Semiquantitative methods which make use of particles of known size, shape and composition as calibration standards may be the most direct and simplest approach to undertake. The present paper describes an empirical method in which glass microspheres were used as a model to show how the ratio of the silicon Kα peak X-ray intensity from the microspheres to that of a bulk sample of the same composition correlated to the mass of the microsphere contained within the cell. Irregular shaped silica particles were also analyzed and a calibration curve was generated from these data.

Lateral resolution of the electron microbeam analysis

1978 ◽  
Vol 36 (1) ◽  
pp. 542-543
Author(s):  
H.J. Dudek
Keyword(s):  
Quantitative Analysis ◽  
Depth Resolution ◽  
Lateral Resolution ◽  
Cylindrical Particle ◽  
Correction Procedure ◽  
X Ray ◽  
Element Concentrations ◽  
Microbeam Analysis ◽  
The Matrix

The chemical inhomogenities in modern materials such as fibers, phases and inclusions, often have diameters in the region of one micrometer. Using electron microbeam analysis for the determination of the element concentrations one has to know the smallest possible diameter of such regions for a given accuracy of the quantitative analysis.In th is paper the correction procedure for the quantitative electron microbeam analysis is extended to a spacial problem to determine the smallest possible measurements of a cylindrical particle P of high D (depth resolution) and diameter L (lateral resolution) embeded in a matrix M and which has to be analysed quantitative with the accuracy q. The mathematical accounts lead to the following form of the characteristic x-ray intens ity of the element i of a particle P embeded in the matrix M in relation to the intensity of a standard S

An example of spectrum imaging used for comparison of EELS quantitative analysis techniques on Al-Li

1991 ◽  
Vol 49 ◽  
pp. 726-727
Author(s):  
John A. Hunt
Keyword(s):  
Quantitative Analysis ◽  
Large Data ◽  
Difference Spectrum ◽  
Large Data Sets ◽  
Foil Thickness ◽  
Data Sets ◽  
Analysis Techniques ◽  
Spectrum Imaging ◽  
Normal Spectrum ◽  
Electron Energy Loss

Spectrum-imaging is a useful technique for comparing different processing methods on very large data sets which are identical for each method. This paper is concerned with comparing methods of electron energy-loss spectroscopy (EELS) quantitative analysis on the Al-Li system. The spectrum-image analyzed here was obtained from an Al-10at%Li foil aged to produce δ' precipitates that can span the foil thickness. Two 1024 channel EELS spectra offset in energy by 1 eV were recorded and stored at each pixel in the 80x80 spectrum-image (25 Mbytes). An energy range of 39-89eV (20 channels/eV) are represented. During processing the spectra are either subtracted to create an artifact corrected difference spectrum, or the energy offset is numerically removed and the spectra are added to create a normal spectrum. The spectrum-images are processed into 2D floating-point images using methods and software described in [1].

The use of a Bent Grid to Improve the take-Off Angle for Electron Probe Analysis

1976 ◽  
Vol 34 ◽  
pp. 360-361
Author(s):  
Delbert E. Philpott ◽  
David Leaffer
Keyword(s):  
Quantitative Analysis ◽  
Tilt Angle ◽  
Count Rate ◽  
Electron Probe ◽  
Open Area ◽  
Electron Probe Analysis ◽  
Background Ratio ◽  
Probe Analysis

There are certain advantages for electron probe analysis if the sample can be tilted directly towards the detector. The count rate is higher, it optimizes the geometry since only one angle need be taken into account for quantitative analysis and the signal to background ratio is improved. The need for less tilt angle may be an advantage because the grid bars are not moved quite as close to each other, leaving a little more open area for observation. Our present detector (EDAX) and microscope (Philips 300) combination precludes moving the detector behind the microscope where it would point directly at the grid. Therefore, the angle of the specimen was changed in order to optimize the geometry between the specimen and the detector.

Solving the mechanisms responsible for organelle behavior in vivo by same-cell correlative light and electron microscopy

1992 ◽  
Vol 50 (1) ◽  
pp. 14-15
Author(s):  
Conly L. Rieder
Keyword(s):  
Electron Microscopy ◽  
Quantitative Analysis ◽  
Light Microscopy ◽  
Living Cell ◽  
Light And Electron Microscopy ◽  
Time Behavior ◽  
Dynamic Interactions ◽  
Positive Identification ◽  
Cellular Components

The behavior of many cellular components, and their dynamic interactions, can be characterized in the living cell with considerable spatial and temporal resolution by video-enhanced light microscopy (video-LM). Indeed, under the appropriate conditions video-LM can be used to determine the real-time behavior of organelles ≤ 25-nm in diameter (e.g., individual microtubules—see). However, when pushed to its limit the structures and components observed within the cell by video-LM cannot be resolved nor necessarily even identified, only detected. Positive identification and a quantitative analysis often requires the corresponding electron microcopy (EM).

Bence-albee after 25 years: A new superior α-factor correction procedure for the quantitative analysis of oxides and silicates

1992 ◽  
Vol 50 (2) ◽  
pp. 1744-1745
Author(s):  
John T. Armstrong
Keyword(s):  
Quantitative Analysis ◽  
Electron Microprobe ◽  
Binary Systems ◽  
Correction Procedure ◽  
Geological Samples ◽  
The Past ◽  
Large Matrix ◽  
Computational Speed ◽  
Microprobe Data ◽  
Geological Sciences

One of the most cited papers in the geological sciences has been that of Albee and Bence on the use of empirical " α -factors" to correct quantitative electron microprobe data. During the past 25 years this method has remained the most commonly used correction for geological samples, despite the facts that few investigators have actually determined empirical α-factors, but instead employ tables of calculated α-factors using one of the conventional "ZAF" correction programs; a number of investigators have shown that the assumption that an α-factor is constant in binary systems where there are large matrix corrections is incorrect (e.g, 2-3); and the procedure’s desirability in terms of program size and computational speed is much less important today because of developments in computing capabilities. The question thus exists whether it is time to honorably retire the Bence-Albee procedure and turn to more modern, robust correction methods. This paper proposes that, although it is perhaps time to retire the original Bence-Albee procedure, it should be replaced by a similar method based on compositiondependent polynomial α-factor expressions.

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