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Energy Dispersive X-ray Tomography for 3D Elemental Mapping of Individual Nanoparticles

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Non-negative matrix factorization-aided phase unmixing and trace element quantification of STEM-EDXS data.

Hui Chen¹, Farhang Nabiei², James Badro³

¹Electron Spectrometry and Microscopy Laboratory (LSME), Institute of Physics (IPHYS), École Polytechnique Fédérale de Lausanne (EPFL), Lausanne CH-1015, Switzerland.

Ultramicroscopy

|May 28, 2024

Summary

This summary is machine-generated.

This study introduces a new semi-automated method combining non-negative matrix factorization and prior knowledge to analyze complex materials using scanning transmission electron microscope-energy-dispersive X-ray spectroscopy (STEM-EDXS) mapping, improving chemical characterization.

Keywords:

Machine learning NMF Phase unmixing STEM-EDXS Trace element quantification

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Area of Science:

Materials Science
Geochemistry
Electron Microscopy

Background:

Scanning transmission electron microscope-energy-dispersive X-ray spectroscopy (STEM-EDXS) is vital for material chemical characterization.
Quantification in STEM-EDXS is difficult for samples with overlapping phases and common elements.
Electron beam-sensitive materials, like those from Earth's deep mantle, pose additional analytical challenges.

Purpose of the Study:

To develop a semi-automated methodology for identifying, segmenting, and unmixing phases with significant spectral and spatial overlap in STEM-EDXS data.
To retrieve accurate energy-dispersive X-ray spectra and phase abundance maps for complex materials.
To enable reliable trace element quantification in challenging sample matrices.

Main Methods:

Combining non-negative matrix factorization (NMF) with a priori knowledge of the sample.
Applying the methodology to an electron beam-sensitive mineral assemblage from Earth's deep mantle.
Semi-automated phase identification, segmentation, and spectral unmixing.

Main Results:

Successfully retrieved true EDX spectra for constituent phases in a complex mineral assemblage.
Generated accurate phase abundance maps, resolving spatial overlap.
Achieved reliable quantification of trace elements down to approximately 100 ppm concentration levels.
Demonstrated the method's effectiveness on an electron beam-sensitive sample.

Conclusions:

The developed methodology effectively overcomes challenges in STEM-EDXS quantification caused by phase overlap and limited signal-to-noise ratio.
This approach enhances the chemical characterization capabilities for diverse materials systems.
The technique is adaptable for analyzing various materials with complex spectral and spatial characteristics.