Exploiting deep learning for predictable carbon dot design
- 10 December 2020
- journal article
- research article
- Published by Royal Society of Chemistry (RSC) in Chemical Communications
- Vol. 57 (4), 532-535
- https://doi.org/10.1039/d0cc07882d
Abstract
In this study, we developed a deep convolution neural network (DCNN) model for predicting the optical properties of carbon dots (CDs), including spectral properties and fluorescence color under ultraviolet irradiation. These results demonstrate the powerful potential of DCNN for guiding the synthesis of CDs.Keywords
Funding Information
- National Natural Science Foundation of China (21977031)
- Science and Technology Commission of Shanghai Municipality (19ZR1472300)
- Fundamental Research Funds for the Central Universities
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