2D_TMD_Quantification_with_Deeplearning

Deep learning-assisted quantification of atomic dopants and defects in two-demensional materials

Sang-Hyeok Yang, Wooseon Choi, Byeong Wook Cho, Frederick Osei-Tutu Agyapong-Fordjour, Sehwan Park, Seok Joon Yun, Hyung-Jin Kim, Young-Kyu Han, Young Hee Lee, Ki Kang Kim, and Young-Min Kim*

Published in Advanced Science (2021) 8 2101099. http://doi.org/10.1002/advs.202101099

It is the code for extracting the quantitative & local information of STEM ADF images of 2D TMDs material(V doped WSe2) using deep neural network. In 'main_test_model.ipynb' file, you can confirm the code in this project.

See also

APL Materials (2023) 11 111124. https://doi.org/10.1063/5.0175469