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Array Tomography Workflow for the Targeted Acquisition of Volume Information using Scanning Electron Microscopy

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Evaluation of different rectangular scan strategies for STEM imaging.

A Velazco¹, M Nord¹, A Béché¹

¹EMAT, University of Antwerp, Groenenborgerlaan 171, 2020 Antwerp, Belgium; NANOlab Center of Excellence, University of Antwerp, Belgium.

Ultramicroscopy

|June 3, 2020

Summary

This study compares STEM imaging scan patterns, finding Hilbert scan offers superior high-frequency detail and reduced bias in lattice parameter measurements, especially with sample drift. Both Hilbert and snake patterns reduce radiation dose compared to traditional raster scanning.

Keywords:

Aberration corrected STEM Drift Hilbert scan pattern Precision Scanning distortions

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Area of Science:

Materials Science
Electron Microscopy
Nanotechnology

Background:

Scanning Transmission Electron Microscopy (STEM) typically uses raster scanning.
Raster scanning can be inefficient and susceptible to sample drift.
Optimizing scan patterns is crucial for high-resolution imaging and accurate analysis.

Purpose of the Study:

To compare the performance of different STEM imaging scan patterns.
To evaluate the impact of scan patterns on image fidelity, especially under sample drift conditions.
To assess the efficiency and accuracy of lattice parameter measurements using various scan patterns.

Main Methods:

Implementation of a programmable scan engine for arbitrary probe path control.
Experimental comparison of raster, snake, and Hilbert scan patterns on a single crystal test sample.
Evaluation of imaging performance based on dwell time, sample drift, and image analysis.

Main Results:

The Hilbert scan pattern more accurately captures high-frequency image content in the presence of sample drift.
Hilbert scanning reduces bias in lattice parameter measurements while maintaining precision.
Both snake and Hilbert scanning offer dose reduction benefits due to smaller probe movement steps compared to raster scanning with flyback correction.

Conclusions:

The Hilbert scan pattern represents a significant advancement for STEM imaging, particularly in challenging conditions like sample drift.
Hilbert scanning enhances the reliability of quantitative measurements, such as lattice parameters and strain analysis.
Optimized scan strategies like Hilbert and snake patterns improve imaging efficiency and data quality in STEM.