Multivariate Statistical Analysis on a SEMEDS Phase Map of Rare Earth Minerals
Joint Authors
Source
Issue
Vol. 2020, Issue 2020 (31 Dec. 2020), pp.1-11, 11 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2020-01-04
Country of Publication
Egypt
No. of Pages
11
Main Subjects
Information Technology and Computer Science
Abstract EN
The scanning electron microscope/X-ray energy dispersive spectrometer (SEM/EDS) system is widely applied to rare earth minerals (REMs) to qualitatively describe their mineralogy and quantitatively determine their composition.
The performance of multivariate statistical analysis on the EDS raw dataset can enhance the efficiency and the accuracy of phase identification.
In this work, the principal component analysis (PCA) and the blind source separation (BSS) algorithms were performed on an EDS map of a REM sample, assisting to achieve an efficient phase map analysis.
The PCA significantly denoised the phase map and was used as a preprocessing step for the following BSS.
The BSS separated the mixed EDS signals into a set of physically interpretable components, bringing convenience to the phase separation and identification.
Through the comparison between the independent component analysis (ICA) and the nonnegative matrix factorization (NMF) algorithms, the NMF was confirmed to be more suitable for the EDS mapping analysis.
American Psychological Association (APA)
Teng, Chaoyi& Gauvin, Raynald. 2020. Multivariate Statistical Analysis on a SEMEDS Phase Map of Rare Earth Minerals. Scanning،Vol. 2020, no. 2020, pp.1-11.
https://search.emarefa.net/detail/BIM-1207394
Modern Language Association (MLA)
Teng, Chaoyi& Gauvin, Raynald. Multivariate Statistical Analysis on a SEMEDS Phase Map of Rare Earth Minerals. Scanning No. 2020 (2020), pp.1-11.
https://search.emarefa.net/detail/BIM-1207394
American Medical Association (AMA)
Teng, Chaoyi& Gauvin, Raynald. Multivariate Statistical Analysis on a SEMEDS Phase Map of Rare Earth Minerals. Scanning. 2020. Vol. 2020, no. 2020, pp.1-11.
https://search.emarefa.net/detail/BIM-1207394
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1207394