Results of quantitative analysis of Celtic glass artefacts by energy dispersive X-ray fluorescence spectrometry

2003 ◽  
Vol 58 (4) ◽  
pp. 627-633 ◽  
Author(s):  
C. Jokubonis ◽  
P. Wobrauschek ◽  
S. Zamini ◽  
M. Karwowski ◽  
G. Trnka ◽  
...  
Author(s):  
Y. Sato ◽  
T. Hashimoto ◽  
M. Ichihashi ◽  
Y. Ueki ◽  
K. Hirose ◽  
...  

Analytical TEMs have two variations in x-ray detector geometry, high and low angle take off. The high take off angle is advantageous for accuracy of quantitative analysis, because the x rays are less absorbed when they go through the sample. The low take off angle geometry enables better sensitivity because of larger detector solid angle.Hitachi HF-2000 cold field emission TEM has two versions; high angle take off and low angle take off. The former allows an energy dispersive x-ray detector above the objective lens. The latter allows the detector beside the objective lens. The x-ray take off angle is 68° for the high take off angle with the specimen held at right angles to the beam, and 22° for the low angle take off. The solid angle is 0.037 sr for the high angle take off, and 0.12 sr for the low angle take off, using a 30 mm2 detector.


2014 ◽  
Vol 43 (2) ◽  
pp. 47-53 ◽  
Author(s):  
Toshio MIYAZAKI ◽  
Shin-ichi YAMASAKI ◽  
Noriyoshi TSUCHIYA ◽  
Satoshi OKUMURA ◽  
Ryoichi YAMADA ◽  
...  

2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Tong Chen ◽  
Xingpu Qi ◽  
Zaiyong Si ◽  
Qianwei Cheng ◽  
Hui Chen

Abstract In this work, a method was established for discriminating geographical origins of wheat flour based on energy dispersive X-ray fluorescence spectrometry (ED-XRF) and chemometrics. 68 wheat flour samples from three different origins were collected and analyzed using ED-XRF technology. Firstly, the principal component analysis method was applied to analyze the feasibility of discrimination and reduce data dimensionality. Then, Competitive Adaptive Reweighted Sampling (CARS) was used to further extract feature variables, and 12 energy variables (corresponding to mineral elements) were identified and selected to characterize the geographical attributes of wheat flour samples. Finally, a non-linear model was constructed using principal component analysis and quadratic discriminant analysis (QDA). The CARS-PCA-QDA model showed that the accuracy of five-fold cross-validation was 84.25%. The results showed that the established method was able to select important energy channel variables effectively and wheat flour could be classified based on geographical origins with chemometrics, which could provide a theoretical basis for unveiling the relationship between mineral element composition and wheat origin.


1977 ◽  
Vol 49 (12) ◽  
pp. 1734-1737 ◽  
Author(s):  
John A. Boslett ◽  
Robert L. R. Towns ◽  
Robert G. Megargle ◽  
Karl H. Pearson ◽  
Thomas C. Furnas

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