Atomic-Scale Insights into the 2D Materials from Aberration-Corrected Scanning Transmission Electron Microscopy: Progress and Future

被引:3
|
作者
Sohn, Woonbae [1 ]
Kim, Miyoung [1 ]
Jang, Ho Won [1 ,2 ]
机构
[1] Seoul Natl Univ, Dept Mat Sci & Engn, Res Inst Adv Mat, Seoul 08826, South Korea
[2] Seoul Natl Univ, Adv Inst Convergence Technol, Suwon 16229, South Korea
来源
SMALL SCIENCE | 2024年 / 4卷 / 02期
基金
新加坡国家研究基金会;
关键词
2D materials; crystal structures; defects; heterostructures; scanning transmission electron microscopy; BEAM-INDUCED TRANSFORMATIONS; IN-SITU OBSERVATIONS; VAPOR-PHASE GROWTH; BLACK PHOSPHORUS; 2-DIMENSIONAL MATERIALS; RADIATION-DAMAGE; EPITAXIAL-GROWTH; IMAGE-ANALYSIS; SOFTWARE TOOL; TRANSITION;
D O I
10.1002/smsc.202300073
中图分类号
TB3 [工程材料学];
学科分类号
0805 ; 080502 ;
摘要
2D crystals are attractive due to their unique atomic, electronic structures, and physiochemical properties, which strongly rely on the synthesis conditions. The atomic structure and presence of defects in the crystal lattice, such as vacancies, dopants, grain boundaries, and edge terminations, significantly influence the properties of 2D materials. Due to its high spatial resolution, aberration-corrected scanning transmission electron microscopy (AC-STEM) has become a powerful tool to provide atomic-scale insights into the crystal structure, defects, heterointerfaces, ferroelectricity, and in situ observations of 2D materials. This review will cover the status of atomic-scale studies on various 2D materials, including graphene, boron nitride, transition metal dichaogenides, MXenes, and phosphorene using AC-STEM. The future perspective of AC-STEM for new findings in 2D materials using machine learning is further discussed. The status of atomic-scale studies on various 2D materials such as graphene, boron nitride, transition metal dichaogenides, MXenes, and phosphorene using aberration-corrected scanning transmission electron microscopy (AC-STEM) is reviewed. Future perspectives for AC-STEM in new findings of 2D materials using in situ observations and machine learning are further discussed.image (c) 2023 WILEY-VCH GmbH
引用
收藏
页数:23
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