Machine learning driven synthesis of few-layered WTe₂ with geometrical control

Machine learning driven synthesis of few-layered WTe₂ with geometrical control

Reducing the lateral scale of two-dimensional (2D) materials to one-dimensional (1D) has attracted substantial research interest not only to achieve competitive electronic applications but also for the exploration of fundamental physical properties. Controllable synthesis of high-quality 1D nanoribb...

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Bibliographic Details
Main Authors: Xu, Manzhang, Tang, Bijun, Lu, Yuhao, Zhu, Chao, Lu, Qianbo, Zheng, Lu, Zhang, Jingyu, Han, Nannan, Fang, Weidong, Guo, Yuxi, Di, Jun, Song, Pin, He, Yongmin, Kang, Lixing, Zhang, Zhiyong, Zhao, Wu, Guan, Cuntai, Wang, Xuewen, Liu, Zheng
Other Authors: School of Materials Science and Engineering
Format: Journal Article
Language:English
Published: 2022
Subjects:
Engineering::Materials
Engineering::Computer science and engineering
Chemical Vapor Deposition
Nanostructures
Online Access:https://hdl.handle.net/10356/159346

Internet

https://hdl.handle.net/10356/159346

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