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Updated: May 15, 2025

Single-Digit Nanometer Electron-Beam Lithography with an Aberration-Corrected Scanning Transmission Electron Microscope
Published on: September 14, 2018
Atomic-Scale Insights into the 2D Materials from Aberration-Corrected Scanning Transmission Electron Microscopy:
Woonbae Sohn1, Miyoung Kim1, Ho Won Jang1,2
1Department of Materials Science and Engineering Research Institute of Advanced Materials Seoul National University Seoul 08826 Republic of Korea.
Aberration-corrected scanning transmission electron microscopy (AC-STEM) offers atomic-scale insights into 2D materials. This review highlights AC-STEM
Area of Science:
- Materials Science
- Nanotechnology
- Solid State Physics
Background:
- Two-dimensional (2D) crystals possess unique properties highly dependent on synthesis conditions.
- Crystal lattice defects like vacancies and dopants significantly impact 2D material properties.
- Understanding atomic structure is crucial for tailoring 2D material performance.
Purpose of the Study:
- To review the application of aberration-corrected scanning transmission electron microscopy (AC-STEM) for atomic-scale characterization of 2D materials.
- To summarize current findings on various 2D materials including graphene, boron nitride, transition metal dichalcogenides, MXenes, and phosphorene.
- To discuss future prospects of AC-STEM in 2D materials research, incorporating machine learning.
Main Methods:
- Utilizing aberration-corrected scanning transmission electron microscopy (AC-STEM) for high-resolution imaging.
- Analyzing atomic structures and defects in diverse 2D crystalline materials.
- Reviewing published studies employing AC-STEM for 2D material investigation.
Main Results:
- AC-STEM provides unprecedented atomic-scale resolution for studying 2D crystal structures.
- Detailed insights into defects, heterointerfaces, and ferroelectricity in 2D materials have been achieved.
- AC-STEM enables in situ observations of dynamic processes in 2D materials.
Conclusions:
- AC-STEM is an indispensable tool for atomic-scale characterization of 2D materials.
- Future research directions include integrating machine learning with AC-STEM for accelerated discovery.
- Continued application of AC-STEM will unlock new possibilities in 2D materials science.
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