Machine-learning-driven synthesis of carbon dots with enhanced quantum yields

• Main Authors: Han, Yu, Tang, Bijun, Wang, Liang, Bao, Hong, Lu, Yuhao, Guan, Cuntai, Zhang, Liang, Le, Mengying, Liu, Zheng, Wu, Minghong
• Other Authors: School of Materials Science and Engineering
• Format: Article
• Language: English
• Published: 2021
• Subjects: Engineering::Materials; Machine Learning; Carbon Dots
• Online Access: https://hdl.handle.net/10356/151050
• Institution: Nanyang Technological University

Knowing the correlation of reaction parameters in the preparation process of carbon dots (CDs) is essential for optimizing the synthesis strategy, exploring exotic properties, and exploiting potential applications. However, the integrated screening experimental data on the synthesis of CDs are huge...