Deep learning based atomic defect detection framework for two-dimensional materials

Defects to popular two-dimensional (2D) transition metal dichalcogenides (TMDs) seriously lower the efficiency of field-effect transistor (FET) and depress the development of 2D materials. These atomic defects are mainly identified and researched by scanning tunneling microscope (STM) because it can...

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Detalles Bibliográficos
Autores principales: Chen, Fu-Xiang Rikudo, Lin, Chia-Yu, Siao, Hui-Ying, Jian, Cheng-Yuan, Yang, Yong-Cheng, Lin, Chun-Liang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2023
Materias:
Data Descriptor
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9929095/
https://www.ncbi.nlm.nih.gov/pubmed/36788235
http://dx.doi.org/10.1038/s41597-023-02004-6

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9929095/
https://www.ncbi.nlm.nih.gov/pubmed/36788235
http://dx.doi.org/10.1038/s41597-023-02004-6

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