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An applied noise model for low-loss EELS maps.

Christian Zietlow1, Jörg K N Lindner1

  • 1Nanopatterning-Nanoanalysis-Photonic Materials Group, Department of Physics, Paderborn University, Warburgerstr. 100, Paderborn, 33098, Germany.

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Summary
This summary is machine-generated.

Understanding noise in electron energy-loss spectroscopy (EELS) is crucial. This study provides a noise model and methods to characterize noise parameters for improved scanning transmission electron microscope (STEM) EELS data quality.

Keywords:
EELS detectorEELS mapsNoise modelNoise parametersPoint spread function EELSZLP alignment

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Area of Science:

  • Materials Science
  • Analytical Chemistry
  • Physics

Background:

  • Electron energy-loss spectroscopy (EELS) in scanning transmission electron microscopy (STEM) is prone to noise and signal blurring.
  • Detector point spread functions (PSF) introduce correlations that smooth noise, impacting data quality.
  • Accurate noise assessment is vital for deconvolution and improving EELS signal enhancement.

Purpose of the Study:

  • To provide theoretical insight into noise smoothing and correlations in EELS.
  • To investigate energy drift and beam current deviation effects in EELS mapping.
  • To develop a practical, applied noise model for EELS measurements.

Main Methods:

  • Mathematical derivation of an applied noise model for EELS.
  • Characterization of noise correlations using Pearson coefficients.
  • Investigation of energy alignment and intensity normalization techniques for EELS mapping.

Main Results:

  • Theoretical understanding of noise smoothing by convolution in EELS.
  • Quantification of noise correlations in EELS detector data.
  • Demonstration of energy drift correction and beam current normalization effects on noise.

Conclusions:

  • A comprehensive understanding of EELS noise is presented.
  • A straightforward, applied noise model is derived for EELS data.
  • Methods are provided for users to determine EELS detector noise parameters.