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Automated Two-dimensional Spatiotemporal Analysis of Mobile Single-molecule FRET Probes

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Complementary ADF-STEM: a Flexible Approach to Quantitative 4D-STEM.

Bryan D Esser¹, Joanne Etheridge²

¹Monash Centre for Electron Microscopy, Monash University, VIC 3800, Australia.

Ultramicroscopy

|November 3, 2022

Summary

This summary is machine-generated.

This study presents a new method for analyzing four-dimensional scanning transmission electron microscopy (4D-STEM) data. It quantifies the full electron beam flux, improving experimental flexibility and image quality.

Keywords:

Annular Dark Field STEM Four-Dimensional Scanning Transmission Electron Microscopy (4D-STEM)Quantitative STEM

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Area of Science:

Materials Science
Electron Microscopy

Background:

Scanning transmission electron microscopy (STEM) is vital for materials characterization across various length scales.
High-speed direct electron detectors enable four-dimensional STEM (4D-STEM) by collecting diffraction patterns at each probe position.
Current 4D-STEM detectors face limitations in angular resolution versus collection angle due to pixel count.

Purpose of the Study:

To develop a straightforward method for quantifying 4D-STEM data.
To utilize the full electron beam flux, including scattered electrons beyond detector limits.
To enhance experimental flexibility and image synthesis in 4D-STEM.

Main Methods:

Quantifying 4D-STEM data by integrating the entire electron beam flux.
Utilizing electrons scattered beyond the detector's angular range.
Developing a method applicable to low-angle diffraction patterns.

Main Results:

Enables synthesis of quantitative, high-contrast complementary annular dark field (cADF) STEM images.
Maintains high angular resolution while improving image contrast.
Allows for optimization of electron dose and better use of low dynamic range detectors.

Conclusions:

The described method significantly increases experimental flexibility in 4D-STEM.
It overcomes limitations of current detector technology, enhancing data quantification.
This approach broadens the applicability and improves the outcomes of 4D-STEM analysis.