5 papers
In-situ Self-optimization of Quantum Dot Emission for Lasers by Machine-Learning Assisted Epitaxy
Chao Shen, Wenkang Zhan, Shujie Pan +12
Traditional methods for optimizing light source emissions rely on a time-consuming trial-and-error approach. While in-situ optimization of light source gain media emission during g…
On-Demand Growth of Semiconductor Heterostructures Guided by Physics-Informed Machine Learning
Chao Shen, Yuan Li, Wenkang Zhan +15
Developing tailored semiconductor heterostructures on demand represents a critical capability for addressing the escalating performance demands in electronic and optoelectronic dev…
Enhanced Radiation Hardness of InAs/GaAs Quantum Dot Lasers for Space Communication
Manyang Li, Jianan Duan, Zhiyong Jin +15
Semiconductor lasers have great potential for space laser communication. However, excessive radiation in space can cause laser failure. In principle, quantum dot (QD) lasers are mo…
Universal Deoxidation of Semiconductor Substrates Assisted by Machine-Learning and Real-Time-Feedback-Control
Chao Shen, Wenkang Zhan, Jian Tang +4
Thin film deposition is an essential step in the semiconductor process. During preparation or loading, the substrate is exposed to the air unavoidably, which has motivated studies…
Epitaxial growth of high-quality GaAs on Si(001) using ultrathin buffer layers
Kun Cheng, Tianyi Tang, Wenkang Zhan +4
The direct growth of III-V semiconductors on silicon holds tremendous potential for photonics applications. However, the inherent differences in their properties lead to defects in…