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

• المؤلفون الرئيسيون: Guo, Huazhang, Lu, Yuhao, Lei, Zhendong, Bao, Hong, Zhang, Mingwan, Wang, Zeming, Guan, Cuntai, Tang, Bijun, Liu, Zheng, Wang, Liang
• مؤلفون آخرون: School of Materials Science and Engineering
• التنسيق: مقال
• اللغة: English
• منشور في: 2024
• الموضوعات: Engineering; Machine learning; Multiobjective optimization
• الوصول للمادة أونلاين: 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...