期刊
CHEMICAL COMMUNICATIONS
卷 58, 期 64, 页码 9014-9017出版社
ROYAL SOC CHEMISTRY
DOI: 10.1039/d2cc03473e
关键词
-
资金
- Natural Science Foundation of China (NSFC) [22134005]
- Natural Science Foundation of Chongqing, China [cstc2021jcyj-msxmX0066]
The study proposes an efficient synthesis method based on machine learning to assist researchers in synthesizing red fluorescent CDs, which can quickly and efficiently predict the predesigned conditions of CD synthesis, avoiding invalid experiments, and improving synthesis efficiency.
Due to their excellent optical properties, red carbon dots (CDs) have been widely used in cell imaging and biomedical therapy. However, the efficiency of red CD synthesis is deficient, and the synthesis cost is high. Here, we propose an efficient synthesis method based on machine learning to assist researchers in synthesizing red fluorescent CDs. This strategy can quickly and efficiently predict the predesigned conditions of CD synthesis. It avoids invalid synthetic experiments and improves the efficiency of red CD synthesis.
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