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Inverse Modeling of Heterogeneous Structures in Electron Probe Microanalysis.

Silvia Richter1, Gaurav Achuda1, Philippe T Pinard2

  • 1Central Facility for Electron Microscopy, RWTH Aachen University, Aachen 52074, Germany.

Microscopy and Microanalysis : the Official Journal of Microscopy Society of America, Microbeam Analysis Society, Microscopical Society of Canada
|July 31, 2024
PubMed
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Electron probe microanalysis (EPMA) now analyzes sub-micrometer structures by acquiring data at multiple positions and energies. This inverse modeling approach reveals chemical composition in fine details previously obscured by excitation volume limitations.

Keywords:
EPMAMonte-Carlo simulationdeterministic modelinverse modeling

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Area of Science:

  • Materials Science
  • Analytical Chemistry
  • Physics

Background:

  • Electron probe microanalysis (EPMA) traditionally characterizes materials at the micrometer scale.
  • Conventional EPMA's spatial resolution is limited by its excitation volume (100 nm to a few µm).
  • Advanced electron sources enable sub-micrometer focused electron beams, necessitating new analytical strategies.

Purpose of the Study:

  • To chemically characterize structures smaller than the EPMA excitation volume.
  • To develop and validate new strategies for high-resolution chemical mapping.
  • To extend inverse modeling techniques for nanoscale chemical analysis.

Main Methods:

  • Acquisition of EPMA data at multiple sample positions and beam energies.
  • Utilizing Monte Carlo simulations and a deterministic model based on Boltzmann equation moment equations.
  • Applying inverse modeling to reconstruct chemical composition from measured data.

Main Results:

  • Demonstrated successful chemical characterization of sub-micrometer structures.
  • Presented inverse modeling strategies for both ill-posed and well-posed problems.
  • Extended the method to reconstruct 2D structures with heterogeneous composition.

Conclusions:

  • New EPMA strategies effectively overcome excitation volume limitations for nanoscale chemical analysis.
  • Inverse modeling provides a powerful approach for high-resolution chemical composition reconstruction.
  • The developed method enables detailed chemical mapping of complex nanoscale materials.