Single-Image-Based Deep Learning for Precise Atomic Defect Identification-Reference-Cited by-同舟云学术

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Single-Image-Based Deep Learning for Precise Atomic Defect Identification

Published:2024-08-06 Issue:33 Volume:24 Page:10275-10283
ISSN:1530-6984
Container-title:Nano Letters
language:en
Short-container-title:Nano Lett.

Author:

Li Kangshu¹^ORCID,Han Xiaocang¹,Meng Yuan¹,Li Junxian¹,Hong Yanhui²,Chen Xiang¹,You Jing-Yang³^ORCID,Yao Lin²,Hu Wenchao¹,Xia Zhiyi²,Ke Guolin²,Zhang Linfeng²⁴,Zhang Jin¹^ORCID,Zhao Xiaoxu¹⁴^ORCID

Affiliation:

1. School of Materials Science and Engineering, Peking University, Beijing 100871, China

2. DP Technology, Beijing 100080, China

3. Department of Physics, National University of Singapore, Singapore 117551

4. AI for Science Institute, Beijing 100084, China

Funder

Beijing National Laboratory for Molecular Sciences

Ministry of Science and Technology of the People's Republic of China

Songshan Lake Materials Laboratory

Science, Technology and Innovation Commission of Shenzhen Municipality

Beijing Municipal Natural Science Foundation

National Natural Science Foundation of China

Chinese Academy of Sciences

Publisher

American Chemical Society (ACS)

Link

https://pubs.acs.org/doi/pdf/10.1021/acs.nanolett.4c02654

Reference43 articles.

1. Disorder-driven non-Fermi liquid behaviour of correlated electrons

2. The Metal-Insulator Transition in Correlated Disordered Systems

3. Visualization of defect induced in-gap states in monolayer MoS2

4. Tuning the Conductivity Type in Monolayer WS 2 and MoS 2 by Sulfur Vacancies

5. Poly(4-styrenesulfonate)-induced sulfur vacancy self-healing strategy for monolayer MoS2 homojunction photodiode

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