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Background subtraction in electron Compton spectroscopy.

B G Mendis1

  • 1Dept. of Physics, Durham University, Durham, DH1 3LE, UK.

Micron (Oxford, England : 1993)
|October 15, 2022
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Summary
This summary is machine-generated.

This study introduces a new method for background subtraction in electron energy loss spectroscopy (EELS) Compton scattering. The technique improves the analysis of electronic state momentum distributions in solids, even with overlapping signals.

Keywords:
Compton scatteringDynamical scatteringFourier log deconvolutionMultislice

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Area of Science:

  • Solid-state physics
  • Materials science
  • Spectroscopy

Background:

  • Compton scattering in EELS quantifies electronic state momentum distributions.
  • Compton signals are broad and have low intensity, leading to poor signal-to-background ratios.
  • Background subtraction is challenging, particularly with overlapping EELS core loss edges.

Purpose of the Study:

  • To develop an empirical background subtraction routine for Compton scattering in EELS.
  • To address the challenge of low signal-to-background ratios and overlapping spectral features.
  • To enable accurate quantification of momentum distributions in solids.

Main Methods:

  • An empirical background subtraction routine was developed.
  • The routine utilizes input data from bright-field EELS spectra without Compton signals.
  • It accounts for multiple elastic-inelastic scattering within EELS collection angles.

Main Results:

  • The background subtraction routine was successfully demonstrated on a silicon Compton profile overlapping with the Si L-edge.
  • The method effectively removes background noise from Compton scattering data.
  • Systematic errors associated with the method were analyzed.

Conclusions:

  • The proposed empirical background subtraction routine is effective for Compton scattering in EELS.
  • This method enhances the analysis of electronic state momentum distributions.
  • The technique offers a solution for challenging spectral overlaps in EELS analysis.