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Depth profiles and resolution limits in accelerator-based solid state analysis.

R Fischer1

  • 1Centre for Interdisciplinary Plasma Science, Max-Planck-Institut für Plasmaphysik, EURATOM Association, 85748 Garching bei München, Germany. rainer.fischer@ipp.mpg.de

Analytical and Bioanalytical Chemistry
|October 25, 2002
PubMed
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Determining elemental composition with depth is challenging. This study uses Bayesian probability theory to solve the ill-posed inversion problem, improving energy resolution for depth profiling in carbon materials.

Area of Science:

  • Solid state analysis
  • Materials science
  • Nuclear physics

Background:

  • Elemental depth profiling is crucial for solid-state analysis but faces challenges.
  • Ion-beam experiments present an ill-posed inversion problem due to various energy-related effects.
  • Accurate depth profiling is essential for understanding material composition and structure.

Purpose of the Study:

  • To address the ill-posed inversion problem in elemental depth profiling.
  • To develop a robust method for reconstructing depth profiles from ion-beam data.
  • To enhance the accuracy and resolution of depth profile determination.

Main Methods:

  • Utilized Bayesian probability theory to solve the inversion problem.
  • Deconvolved the apparatus transfer function to account for experimental artifacts.

Related Experiment Videos

  • Modeled scattering events within the sample material.
  • Applied the method to analyze carbon-13 in tetrahedral amorphous carbon and carbon-12/carbon-13 marker probes.

    • Main Results:

    • Successfully reconstructed depth profiles of carbon-13 in tetrahedral amorphous carbon.
    • Determined depth profiles in carbon-12/carbon-13 marker probe samples.
    • Achieved a significant enhancement in energy resolution by a factor of six.
    • Demonstrated the effectiveness of Bayesian inference for complex depth profiling.

    Conclusions:

    • Bayesian probability theory offers a powerful framework for solving ill-posed inversion problems in depth profiling.
    • The developed method significantly improves energy resolution and accuracy in elemental composition analysis.
    • This approach provides a reliable tool for characterizing material composition as a function of depth.