Autonomous, Self-driving Multi-Step Growth of Semiconductor Heterostructures Guided by Machine Learning

no code implementations • 7 Aug 2024 • Chao Shen, Wenkang Zhan, Hongyu Sun, Kaiyao Xin, Bo Xu, Zhanguo Wang, Chao Zhao

The semiconductor industry has prioritized automating repetitive tasks by closed-loop, autonomous experimentation which enables accelerated optimization of complex multi-step processes.

Machine-Learning-Assisted and Real-Time-Feedback-Controlled Growth of InAs/GaAs Quantum Dots

no code implementations • 22 Jun 2023 • Chao Shen, Wenkang Zhan, Kaiyao Xin, Manyang Li, Zhenyu Sun, Hui Cong, Chi Xu, Jian Tang, Zhaofeng Wu, Bo Xu, Zhongming Wei, Chunlai Xue, Chao Zhao, Zhanguo Wang

Self-assembled InAs/GaAs quantum dots (QDs) have properties highly valuable for developing various optoelectronic devices such as QD lasers and single photon sources.