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

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

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...

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Bibliographic Details
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: Journal Article
Language:English
Published: 2021
Subjects:
Engineering::Materials
Machine Learning
Carbon Dots
Online Access:https://hdl.handle.net/10356/151050

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