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Inverse modeling for quantitative X-ray microanalysis applied to 2D heterogeneous materials.

Yu Yuan1, Hendrix Demers2, Nicolas Brodusch1

  • 1Department of Mining and Materials Engineering, McGill University, 3610 Rue University, Montreal, Québec, Canada, H3A 0C5.

Ultramicroscopy
|September 28, 2020
PubMed
Summary

This study introduces a new inverse modeling algorithm for analyzing heterogeneous materials using X-ray microanalysis. The method accurately determines material structure and composition in 2D samples, advancing quantitative analysis.

Keywords:
2D heterogeneous materialsInverse modelingMonte Carlo simulationStructure and composition determinationVoxel-based specimenX-ray microanalysis

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Area of Science:

  • Materials Science
  • Analytical Chemistry
  • Computational Modeling

Background:

  • Current quantitative X-ray microanalysis is limited to homogeneous materials.
  • Analyzing heterogeneous materials requires advanced techniques for structure and composition determination.

Purpose of the Study:

  • To develop and validate an inverse modeling algorithm for analyzing 2D heterogeneous materials.
  • To determine both the structure and composition of complex samples using X-ray intensity measurements.

Main Methods:

  • An iterative inverse modeling approach combined with forward modeling using the Monte Carlo method.
  • Acquisition of X-ray intensity data at varying beam energies and positions.
  • Minimization of differences between simulated and experimental characteristic X-ray intensities.

Main Results:

  • The algorithm successfully determined the structure and composition of 1D and 2D phantom samples.
  • Good agreement was observed between simulated and experimental results for most sample regions.
  • Minor discrepancies were noted in deeper voxels of 2D samples, potentially due to simulation or X-ray range variations.

Conclusions:

  • The developed inverse modeling algorithm is feasible for analyzing 2D heterogeneous materials.
  • This method offers a promising approach for quantitative X-ray microanalysis of complex materials.
  • Further refinement may address discrepancies at greater depths.