AtomGAN: unsupervised deep learning for fast and accurate defect detection of 2D materials at the atomic scale
Author:
Publisher
Springer Science and Business Media LLC
Subject
General Computer Science
Link
https://link.springer.com/content/pdf/10.1007/s11432-022-3757-x.pdf
Reference31 articles.
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4. Fu L, Li H, Wang L, et al. Defect passivation strategies in perovskites for an enhanced photovoltaic performance. Energy Environ Sci, 2020, 13: 4017–4056
5. Sangwan V K, Jariwala D, Kim I S, et al. Gate-tunable memristive phenomena mediated by grain boundaries in single-layer MoS2. Nat Nanotech, 2015, 10: 403–406
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