Cargando…

In Situ Scanning Transmission Electron Microscopy Study of MoS(2) Formation on Graphene with a Deep-Learning Framework

[Image: see text] Atomic-scale information is essential for understanding and designing unique structures and properties of two-dimensional (2D) materials. Recent developments in in situ transmission electron microscopy (TEM) and scanning transmission electron microscopy (STEM) enable research to pr...

Descripción completa

Detalles Bibliográficos
Autores principales: Lee, Yeongdong, Lee, Jongyeong, Chung, Handolsam, Kim, Jaemin, Lee, Zonghoon
Formato: Online Artículo Texto
Lenguaje:English
Publicado: American Chemical Society 2021
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8388093/
https://www.ncbi.nlm.nih.gov/pubmed/34471766
http://dx.doi.org/10.1021/acsomega.1c03002
_version_ 1783742575195193344
author Lee, Yeongdong
Lee, Jongyeong
Chung, Handolsam
Kim, Jaemin
Lee, Zonghoon
author_facet Lee, Yeongdong
Lee, Jongyeong
Chung, Handolsam
Kim, Jaemin
Lee, Zonghoon
author_sort Lee, Yeongdong
collection PubMed
description [Image: see text] Atomic-scale information is essential for understanding and designing unique structures and properties of two-dimensional (2D) materials. Recent developments in in situ transmission electron microscopy (TEM) and scanning transmission electron microscopy (STEM) enable research to provide abundant insights into the growth of nanomaterials. In this study, 2D MoS(2) is synthesized on a suspended graphene substrate inside a TEM column through thermolysis of the ammonium tetrathiomolybdate (NH(4))(2)MoS(4) precursor at 500 °C. To avoid misinterpretation of the in situ STEM images, a deep-learning framework, DeepSTEM, is developed. The DeepSTEM framework successfully reconstructs an object function in atomic-resolution STEM imaging for accurate determination of the atomic structure and dynamic analysis. In situ STEM imaging with DeepSTEM enables observation of the edge configuration, formation, and reknitting progress of MoS(2) clusters with the formation of a mirror twin boundary. The synthesized MoS(2)/graphene heterostructure shows various twist angles, as revealed by atomic-resolution TEM. This deep-learning framework-assisted in situ STEM imaging provides atomic information for in-depth studies on the growth and structure of 2D materials and shows the potential use of deep-learning techniques in 2D material research.
format Online
Article
Text
id pubmed-8388093
institution National Center for Biotechnology Information
language English
publishDate 2021
publisher American Chemical Society
record_format MEDLINE/PubMed
spelling pubmed-83880932021-08-31 In Situ Scanning Transmission Electron Microscopy Study of MoS(2) Formation on Graphene with a Deep-Learning Framework Lee, Yeongdong Lee, Jongyeong Chung, Handolsam Kim, Jaemin Lee, Zonghoon ACS Omega [Image: see text] Atomic-scale information is essential for understanding and designing unique structures and properties of two-dimensional (2D) materials. Recent developments in in situ transmission electron microscopy (TEM) and scanning transmission electron microscopy (STEM) enable research to provide abundant insights into the growth of nanomaterials. In this study, 2D MoS(2) is synthesized on a suspended graphene substrate inside a TEM column through thermolysis of the ammonium tetrathiomolybdate (NH(4))(2)MoS(4) precursor at 500 °C. To avoid misinterpretation of the in situ STEM images, a deep-learning framework, DeepSTEM, is developed. The DeepSTEM framework successfully reconstructs an object function in atomic-resolution STEM imaging for accurate determination of the atomic structure and dynamic analysis. In situ STEM imaging with DeepSTEM enables observation of the edge configuration, formation, and reknitting progress of MoS(2) clusters with the formation of a mirror twin boundary. The synthesized MoS(2)/graphene heterostructure shows various twist angles, as revealed by atomic-resolution TEM. This deep-learning framework-assisted in situ STEM imaging provides atomic information for in-depth studies on the growth and structure of 2D materials and shows the potential use of deep-learning techniques in 2D material research. American Chemical Society 2021-08-10 /pmc/articles/PMC8388093/ /pubmed/34471766 http://dx.doi.org/10.1021/acsomega.1c03002 Text en © 2021 The Authors. Published by American Chemical Society https://creativecommons.org/licenses/by-nc-nd/4.0/Permits non-commercial access and re-use, provided that author attribution and integrity are maintained; but does not permit creation of adaptations or other derivative works (https://creativecommons.org/licenses/by-nc-nd/4.0/).
spellingShingle Lee, Yeongdong
Lee, Jongyeong
Chung, Handolsam
Kim, Jaemin
Lee, Zonghoon
In Situ Scanning Transmission Electron Microscopy Study of MoS(2) Formation on Graphene with a Deep-Learning Framework
title In Situ Scanning Transmission Electron Microscopy Study of MoS(2) Formation on Graphene with a Deep-Learning Framework
title_full In Situ Scanning Transmission Electron Microscopy Study of MoS(2) Formation on Graphene with a Deep-Learning Framework
title_fullStr In Situ Scanning Transmission Electron Microscopy Study of MoS(2) Formation on Graphene with a Deep-Learning Framework
title_full_unstemmed In Situ Scanning Transmission Electron Microscopy Study of MoS(2) Formation on Graphene with a Deep-Learning Framework
title_short In Situ Scanning Transmission Electron Microscopy Study of MoS(2) Formation on Graphene with a Deep-Learning Framework
title_sort in situ scanning transmission electron microscopy study of mos(2) formation on graphene with a deep-learning framework
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8388093/
https://www.ncbi.nlm.nih.gov/pubmed/34471766
http://dx.doi.org/10.1021/acsomega.1c03002
work_keys_str_mv AT leeyeongdong insituscanningtransmissionelectronmicroscopystudyofmos2formationongraphenewithadeeplearningframework
AT leejongyeong insituscanningtransmissionelectronmicroscopystudyofmos2formationongraphenewithadeeplearningframework
AT chunghandolsam insituscanningtransmissionelectronmicroscopystudyofmos2formationongraphenewithadeeplearningframework
AT kimjaemin insituscanningtransmissionelectronmicroscopystudyofmos2formationongraphenewithadeeplearningframework
AT leezonghoon insituscanningtransmissionelectronmicroscopystudyofmos2formationongraphenewithadeeplearningframework