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Atom column detection from simultaneously acquired ABF and ADF STEM images.

J Fatermans1, A J den Dekker2, K Müller-Caspary3

  • 1Electron Microscopy for Materials Science (EMAT), University of Antwerp, Groenenborgerlaan 171, 2020 Antwerp, Belgium; NANOlab Center of Excellence, University of Antwerp, Belgium; imec-Vision Lab, University of Antwerp, Universiteitsplein 1, 2610 Wilrijk, Belgium.

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Summary
This summary is machine-generated.

The maximum a posteriori (MAP) probability rule now enhances atomic structure determination in scanning transmission electron microscopy (STEM) for both annular dark-field (ADF) and annular bright-field (ABF) imaging. This method improves light-element detection in nanomaterials with low signal quality.

Keywords:
Annular bright-field (ABF)Annular dark-field (ADF)Maximum a posteriori (MAP) probabilityScanning transmission electron microscopy (STEM)Statistical parameter estimation

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Area of Science:

  • Materials Science
  • Physics
  • Chemistry

Background:

  • High-resolution imaging in scanning transmission electron microscopy (STEM) often suffers from low contrast-to-noise ratio (CNR), particularly in annular dark-field (ADF) and annular bright-field (ABF) modes.
  • Annular bright-field STEM is crucial for visualizing light elements, but these materials are sensitive to electron beams, necessitating low electron doses and resulting in low CNR images.
  • The maximum a posteriori (MAP) probability rule has been previously applied to ADF STEM for atomic structure determination.

Purpose of the Study:

  • To extend the maximum a posteriori (MAP) probability rule methodology for atomic structure determination to annular bright-field (ABF) scanning transmission electron microscopy (STEM) imaging.
  • To enable simultaneous application of the MAP rule to both ABF and annular dark-field (ADF) STEM images.
  • To improve the detection of light elements within nanomaterials, especially those with low contrast-to-noise ratio (CNR).

Main Methods:

  • Development of an extended parametric model for STEM imaging that incorporates the effect of specimen tilt.
  • Application of statistical parameter estimation theory and model-order selection within the MAP probability rule framework.
  • Validation of the methodology using both simulated and experimental annular bright-field (ABF) and annular dark-field (ADF) STEM data.

Main Results:

  • The proposed methodology successfully extends the MAP probability rule to simultaneously analyze ABF and ADF STEM images.
  • The inclusion of specimen tilt effects in the extended parametric model enhances the accuracy of intensity analysis, particularly for ABF STEM.
  • The methodology demonstrates effective detection of light elements in the presence of heavy elements, even with low CNR images.

Conclusions:

  • The extended MAP probability rule provides a robust framework for atomic structure determination in STEM, applicable to both ABF and ADF imaging modes.
  • This approach significantly improves the capability to identify light elements in advanced nanomaterials where electron dose limitations lead to low CNR.
  • The study validates the utility of the MAP rule for analyzing simultaneously acquired ABF/ADF STEM data, advancing materials characterization techniques.