Machine learning-guided realization of full-color high-quantum-yield carbon quantum dots

• Main Authors: Guo, Huazhang, Lu, Yuhao, Lei, Zhendong, Bao, Hong, Zhang, Mingwan, Wang, Zeming, Guan, Cuntai, Tang, Bijun, Liu, Zheng, Wang, Liang
• 其他作者: School of Materials Science and Engineering
• 格式: Article
• 語言: English
• 出版: 2024
• 主題: Engineering; Machine learning; Multiobjective optimization
• 在線閱讀: https://hdl.handle.net/10356/178818

Carbon quantum dots (CQDs) have versatile applications in luminescence, whereas identifying optimal synthesis conditions has been challenging due to numerous synthesis parameters and multiple desired outcomes, creating an enormous search space. In this study, we present a novel multi-objective optim...