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Application of Factorisation Methods to Analysis of Elemental Distribution Maps Acquired with a Full-Field XRF
Bartłomiej Łach1, Tomasz Fiutowski1, Stefan Koperny1
1Faculty of Physics and Applied Computer Science, AGH University of Science and Technology, al. Mickiewicza 30, 30-059 Kraków, Poland.
Sensors (Basel, Switzerland)
|December 10, 2021
Summary
Factor analysis methods like Principal Component Analysis (PCA) and Non-Negative Matrix Factorisation (NMF) enhance elemental analysis selectivity for X-ray Fluorescence (XRF) data, especially with limited detector energy resolution.
Area of Science:
- Materials Science
- Analytical Chemistry
- Spectroscopy
Background:
- Full-field X-ray Fluorescence (XRF) imaging offers elemental distribution mapping.
- Gas Electron Multiplier (GEM) detectors provide position-sensitive detection but have limited energy resolution (18% FWHM at 5.9 keV).
- Processing XRF data with limited energy resolution poses challenges for accurate elemental analysis.
Purpose of the Study:
- To investigate the application of factor analysis methods for processing XRF data from a full-field imaging spectrometer with a GEM detector.
- To evaluate the performance of Principal Component Analysis (PCA) and Non-Negative Matrix Factorisation (NMF) in enhancing elemental analysis selectivity.
- To present the design and results of a developed full-field XRF imaging spectrometer.
Main Methods:
- Design and performance evaluation of a full-field XRF imaging spectrometer utilizing a GEM detector.
- Data calibration and analysis procedures for XRF imaging.
- Elemental mapping using Region of Interest (ROI), Non-Negative Matrix Factorisation (NMF), and Principal Component Analysis (PCA).
Main Results:
- The developed full-field XRF imaging spectrometer was successfully employed for case studies on historical paintings.
- Factor analysis methods, specifically NMF and PCA, demonstrated significant enhancement in elemental analysis selectivity.
- These methods proved effective in overcoming the limitations of low energy resolution from the GEM detector.
Conclusions:
- Factor analysis methods (NMF and PCA) are highly effective for processing XRF data from spectrometers with limited energy resolution.
- The developed full-field XRF imaging spectrometer, combined with NMF and PCA, provides enhanced capabilities for elemental distribution analysis.
- This approach is particularly valuable for analyzing complex samples like historical artifacts where detailed elemental mapping is crucial.
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