Ad hoc auto-tuning of aberrations using high-resolution STEM images by autocorrelation function

Area of Science:

• Materials Science
• Electron Microscopy
• Optics

Background:

• Aberrations in electron microscopy limit image resolution.
• Accurate measurement of aberrations is crucial for high-resolution imaging.
• Current methods for aberration correction can be complex and time-consuming.

Purpose of the Study:

• To develop a novel method for measuring aberration status using dark-field STEM images.
• To enable automated feedback correction of microscope aberrations.
• To improve the accuracy and efficiency of aberration correction in STEM.

Main Methods:

• Utilized scanning transmission electron microscopy (STEM) with high-resolution dark-field imaging.
• Developed the Segmented Image Autocorrelation function Matrix (SIAM) method.
• Employed autocorrelation functions on segmented areas of defocused STEM images from crystalline specimens.

Main Results:

• Successfully measured defocus and twofold astigmatism of the probe-forming system.
• Demonstrated direct feedback of measured values to adjust stigmator and objective lens.
• Achieved automated correction of defocus and twofold astigmatism through iterative feedback.

Conclusions:

• The SIAM method provides an effective means for aberration measurement in STEM.
• Automated aberration correction using SIAM enhances microscope performance.
• This technique facilitates routine high-resolution imaging by simplifying aberration management.