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Quantitative alignment parameter estimation for analyzing X-ray photoelectron spectra.

Matthew Ozon1, Konstantin Tumashevich1, Nønne L Prisle1

  • 1Center for Atmospheric Research, PO BOX 4500, University of Oulu, Finland.

Journal of Synchrotron Radiation
|June 16, 2023
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Summary
This summary is machine-generated.

This study introduces a new method to estimate the alignment parameter in X-ray photoelectron spectroscopy (XPS) using raw spectral data. This advancement allows for more accurate quantitative analysis of XPS, improving material characterization.

Keywords:
X-ray photoelectron spectroscopyexperimental alignment parameterliquid jetmeasurement modelquantitative data inversion

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Area of Science:

  • Surface science
  • Materials characterization
  • Spectroscopy

Background:

  • X-ray photoelectron spectroscopy (XPS) data interpretation relies on measurement models with unknown parameters.
  • The alignment parameter, crucial for understanding light-sample interaction, cannot be directly measured.
  • Existing methods use proxies to estimate experimental alignment, which may lack accuracy.

Purpose of the Study:

  • To develop a method for estimating the absolute value of the alignment parameter in XPS.
  • To enable quantitative analysis of XPS spectra using a simplified measurement model.
  • To validate the method using simulated and experimental XPS data.

Main Methods:

  • Estimation of the alignment parameter using raw XPS spectra, sample geometry, and photoelectron attenuation length.
  • Utilizing the open-source Julia language framework PROPHESY for computations.
  • Testing the method on simulated data with known parameters and subsequently on experimental XPS data.

Main Results:

  • A novel method for estimating the absolute alignment parameter was successfully developed.
  • The method enables quantitative XPS analysis with a simplified measurement model.
  • A strong correlation was observed between the estimated alignment parameter and the commonly used alignment proxy in experimental data.

Conclusions:

  • The proposed method provides a reliable way to determine the alignment parameter in XPS.
  • This facilitates more accurate quantitative analysis of XPS data.
  • The approach is computationally accessible via the PROPHESY framework.