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High temporal-resolution scanning transmission electron microscopy using sparse-serpentine scan pathways.

Eduardo Ortega1, Daniel Nicholls2, Nigel D Browning2,3

  • 1INM - Leibniz Institute for New Materials, 66123, Saarbrucken, Germany.

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|November 23, 2021
PubMed
Summary
This summary is machine-generated.

High-speed scanning transmission electron microscopy (STEM) was achieved by eliminating dead time and using sparse imaging. This method accelerates data acquisition for sensitive materials and single-particle tracking.

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Area of Science:

  • Materials Science
  • Microscopy
  • Physics

Background:

  • Scanning transmission electron microscopy (STEM) offers sub-angstrom resolution for structural analysis.
  • Pixel-by-pixel scanning limits data acquisition speed in STEM.
  • Optimizing scanning strategies is crucial for high-speed imaging and minimizing beam damage.

Purpose of the Study:

  • To significantly increase scanning speeds in STEM.
  • To reduce image acquisition dead time and the number of scanning pixels.
  • To develop a method applicable to radiation-sensitive materials and single-particle tracking.

Main Methods:

  • Eliminated image acquisition dead time caused by beam flyback.
  • Reduced scanning pixels using sparse imaging techniques.
  • Developed a calibration procedure to compensate for magnetic scan coil hysteresis.

Main Results:

  • Achieved frame rates of 92 s⁻¹, 23 s⁻¹, and 5.8 s⁻¹ for 128, 256, and 512 pixel wide images, respectively.
  • Successfully tested sparse and serpentine scanning routines on crystalline thin films, gold nanoparticles, and in-situ liquid phase STEM experiments.
  • Demonstrated a method for high-speed data acquisition in STEM without compromising resolution.

Conclusions:

  • The developed method enables the highest possible scanning speeds in STEM by overcoming traditional limitations.
  • This approach is versatile and can be applied to various samples, including radiation-sensitive materials.
  • The technique is suitable for advanced applications like single-particle tracking and dynamic material analysis.