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Quantification of STEM Images in High Resolution SEM for Segmented and Pixelated Detectors.

Ivo Konvalina1, Aleš Paták1, Martin Zouhar1

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Summary

This study introduces a new method for comparing transmitted electron detector measurements and simulations in ultrahigh resolution scanning electron microscopy. This technique aids in analyzing sample composition and thickness.

Keywords:
Monte Carlo simulationsSTEM segmented detectorpixelated detectorquantitative imagingray tracingscanning electron microscopy

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Area of Science:

  • Materials Science
  • Electron Microscopy
  • Physics

Background:

  • Segmented semiconductor detectors in ultrahigh resolution scanning electron microscopes (UHR-SEM) enable diverse imaging modes.
  • Standard modes (with/without magnetic field) and beam deceleration mode (with electrostatic field) influence transmitted electron trajectories.

Purpose of the Study:

  • To quantify measured images and theoretically study detector segment signal collection capabilities.
  • To develop a new method for improved comparison between experimental measurements and ray-traced simulations.
  • To analyze data from 2D pixel array detectors (PAD) for detailed angular profiling.

Main Methods:

  • Development of a novel method for comparing experimental and simulated transmitted electron data using calibration curves.
  • Acquisition and analysis of measurements using a 2D pixel array detector (PAD).
  • Ray-tracing simulations to model electron trajectories and detector response.

Main Results:

  • Demonstrated that radial profiles from STEM and 2D-PAD data are sensitive to sample material composition.
  • Showcased that scattering processes are influenced by sample thickness.
  • Established a basis for comparing experimental and simulation data for material and thickness estimation.

Conclusions:

  • The new method facilitates more accurate comparison of experimental and simulation data in UHR-SEM.
  • Radial profiles obtained from STEM and 2D-PAD are valuable indicators of sample properties.
  • Accurate comparison of experimental and simulation data can lead to estimations of sample composition and thickness.