Toward Precise n-Type Doping Control in MOVPE-Grown β-Ga<sub>2</sub>O<sub>3</sub> Thin Films by Deep-Learning Approach
In this work, we train a hybrid deep-learning model (fDNN, Forest Deep Neural Network) to predict the doping level measured from the Hall Effect measurement at room temperature and to investigate the doping behavior of Si dopant in both (100) and (010) β-Ga<sub>2</sub>O<sub>3</s...
Main Authors: | Ta-Shun Chou, Saud Bin Anooz, Raimund Grüneberg, Klaus Irmscher, Natasha Dropka, Jana Rehm, Thi Thuy Vi Tran, Wolfram Miller, Palvan Seyidov, Martin Albrecht, Andreas Popp |
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Format: | Article |
Language: | English |
Published: |
MDPI AG
2021-12-01
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Series: | Crystals |
Subjects: | |
Online Access: | https://www.mdpi.com/2073-4352/12/1/8 |
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