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A fast and simple method for background removal in Auger electron spectroscopy.

H E Bauer1

  • 1Institut für Physik der Universität Hohenheim, Garbenstrasse 30, D-70593, Stuttgart, Germany.

Analytical and Bioanalytical Chemistry
|October 1, 1995
PubMed
Summary

A novel formal method efficiently removes background noise in electron beam induced Auger electron spectroscopy. This technique ensures positive spectral values and simplifies peak identification without complex fitting.

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Area of Science:

  • Materials Science
  • Surface Science
  • Spectroscopy

Background:

  • Background removal is crucial for accurate analysis in Electron Beam Induced Auger Electron Spectroscopy (EIAES).
  • Existing methods often require complex fitting procedures or can lead to inaccuracies like negative spectral values.
  • Backscattered electrons contribute significantly to spectral background, complicating quantitative analysis.

Purpose of the Study:

  • To present a purely formal and practical method for background removal in EIAES.
  • To develop a method that avoids the need for spectral fitting.
  • To ensure the resulting spectra are physically meaningful with non-negative values.

Main Methods:

  • A purely formal mathematical approach is applied to recorded Auger electron spectra.

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  • The method processes complete spectra, directly addressing the background signal.
  • No iterative fitting or complex parameterization is required.

    • Main Results:

    • The developed method effectively removes the background without requiring spectral fitting.
    • The background-subtracted spectra consistently yield non-negative values, preventing overcompensation.
    • Auger peaks are clearly resolved and separated by zeros, facilitating subsequent analysis.

    Conclusions:

    • This formal background removal method offers a practical and accurate solution for EIAES data processing.
    • The technique enhances the reliability of peak identification and quantification in Auger electron spectroscopy.
    • The method's simplicity and robustness make it suitable for routine application in surface analysis.