Combining Selective Sequential Extractions, X-ray Absorption Spectroscopy, and Principal Component Analysis for Quantitative Zinc Speciation in Soil

2002 ◽  
Vol 36 (23) ◽  
pp. 5021-5028 ◽  
Author(s):  
Andreas C. Scheinost ◽  
Ruben Kretzschmar ◽  
Sabina Pfister ◽  
Darryl R. Roberts
Keyword(s):  
Principal Component Analysis ◽  
Absorption Spectroscopy ◽  
Principal Component ◽  
Component Analysis ◽  
Sequential Extractions ◽  
X Ray ◽  
Zinc Speciation ◽  
X Ray Absorption

scholarly journals Principal component analysis: Reveal camouflaged information in x-ray absorption spectroscopy photoemission electron microscopy of complex thin oxide films

2018 ◽  
Vol 665 ◽  
pp. 75-84 ◽  
Author(s):  
Margret Giesen ◽  
Matteo Jugovac ◽  
Giovanni Zamborlini ◽  
Vitaliy Feyer ◽  
Felix Gunkel ◽  
...  
Keyword(s):  
Electron Microscopy ◽  
Principal Component Analysis ◽  
Absorption Spectroscopy ◽  
Oxide Films ◽  
Principal Component ◽  
Component Analysis ◽  
X Ray ◽  
Thin Oxide Films ◽  
X Ray Absorption ◽  
Photoemission Electron

Vanadium K-Edge X-ray Absorption Spectroscopy as a Probe of the Heterogeneous Lithiation of V2O5: First-Principles Modeling and Principal Component Analysis

2016 ◽  
Vol 120 (42) ◽  
pp. 23922-23932 ◽  
Author(s):  
Gregory A. Horrocks ◽  
Erick J. Braham ◽  
Yufeng Liang ◽  
Luis R. De Jesus ◽  
Joshua Jude ◽  
...  
Keyword(s):  
Principal Component Analysis ◽  
Absorption Spectroscopy ◽  
First Principles ◽  
Principal Component ◽  
Component Analysis ◽  
X Ray ◽  
X Ray Absorption

scholarly journals XAS studies of Se speciation in selenite-fed rats

Metallomics ◽  
2014 ◽  
Vol 6 (12) ◽  
pp. 2193-2203 ◽  
Author(s):  
Claire M. Weekley ◽  
Jade B. Aitken ◽  
Paul K. Witting ◽  
Hugh H. Harris
Keyword(s):  
Principal Component Analysis ◽  
Absorption Spectra ◽  
Principal Component ◽  
Component Analysis ◽  
Selenium Speciation ◽  
X Ray ◽  
X Ray Absorption ◽  
Se Speciation

An investigation of selenium speciation in the tissues of selenite-fed rats by principal component analysis of X-ray absorption spectra.

An energy dispersive X-ray fluorescence spectrometry approach for the identification of geographical origin of wheat flour

2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Tong Chen ◽  
Xingpu Qi ◽  
Zaiyong Si ◽  
Qianwei Cheng ◽  
Hui Chen
Keyword(s):  
Principal Component Analysis ◽  
Wheat Flour ◽  
Principal Component ◽  
Component Analysis ◽  
Mineral Elements ◽  
Energy Dispersive ◽  
Fluorescence Spectrometry ◽  
Energy Channel ◽  
X Ray ◽  
Different Origins

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.

scholarly journals Combining selective sequential extractions, X-Ray Absorption Spectroscopy, and X-Ray Powder Diffraction for Cu (II) speciation in soil and mineral phases

2017 ◽  
Vol 6 (2) ◽  
pp. 114-114 ◽  
Author(s):  
Tatiana Minkina ◽  
Dina Nevidomskaya ◽  
Alexander Soldatov ◽  
David Pinskii ◽  
Fariz Mikailsoy ◽  
...  
Keyword(s):  
Absorption Spectroscopy ◽  
Powder Diffraction ◽  
Sequential Extractions ◽  
X Ray ◽  
Mineral Phases ◽  
X Ray Absorption

Plastic Classification with X-ray Absorption Spectroscopy Based on Back Propagation Neural Network

2017 ◽  
Vol 71 (11) ◽  
pp. 2538-2548 ◽  
Author(s):  
Qian Wang ◽  
Xiaomei Wu ◽  
Lingcong Chen ◽  
Zheng Yang ◽  
Zheng Fang
Keyword(s):  
Absorption Spectroscopy ◽  
Recognition Rate ◽  
Back Propagation ◽  
Principal Component ◽  
Back Propagation Neural Network ◽  
X Ray ◽  
Analysis Methods ◽  
Average Recognition Rate ◽  
The Stability ◽  
X Ray Absorption

Currently, spectral analysis methods used in the classification of plastics have limitations that do not apply to opaque plastics or the stability of experimental results is not strong. In this paper, X-ray absorption spectroscopy (XAS) has been applied to classify plastics due to its strong penetrability and stability. Fifteen kinds of plastics are selected as specimens. X-ray, which is excited by a voltage of 60 kV, penetrated these specimens. The spectral data acquired by CdTe X-ray detector are processed by principal component analysis (PCA) and other data analysis methods. Then the back propagation neural networks (BPNN) algorithm is used to classify the processed data. The average recognition rate reached 96.95% and classification results of all types of plastic results were analyzed in detail. It indicates that XAS has the potential to classify plastics and that XAS can be used in some fields such as plastic waste sorting and recycling. At the same time, the technology of XAS, in the future, can also be used to classify more substances.

scholarly journals Principal Component Analysis of Multiwavelength Properties of Seyfert Galaxies

1994 ◽  
Vol 159 ◽  
pp. 502-502
Author(s):  
Deborah Dultzin–Hacyan ◽  
Carlos Ruano
Keyword(s):  
Principal Component Analysis ◽  
Statistical Analysis ◽  
Principal Component ◽  
Seyfert Galaxies ◽  
Component Analysis ◽  
X Ray ◽  
Radio Data

A multidimensional statistical analysis of observed properties of Seyfert galaxies has been carried out using Principal Component Analysis (PCA) applied to X-ray, optical, near and far IR and radio data for all the Seyfert galaxies types 1 and 2 for the catalog by Lipovtsky et al. (1987).

Enhancing the Signal-to-Noise Ratio of X-ray Diffraction Profiles by Smoothed Principal Component Analysis

2005 ◽  
Vol 77 (20) ◽  
pp. 6563-6570 ◽  
Author(s):  
Zeng Ping Chen ◽  
Julian Morris ◽  
Elaine Martin ◽  
Robert B. Hammond ◽  
Xiaojun Lai ◽  
...  
Keyword(s):  
Principal Component Analysis ◽  
Signal To Noise Ratio ◽  
Principal Component ◽  
Component Analysis ◽  
X Ray Diffraction ◽  
Signal To Noise ◽  
X Ray ◽  
Noise Ratio
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