Wang XY, Chen BB, Zhang J, Zhou ZR, Lv J, Geng XP, Qian RC. Exploiting deep learning for predictable carbon dot design.
Chem Commun (Camb) 2020;
57:532-535. [PMID:
33336670 DOI:
10.1039/d0cc07882d]
[Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/17/2022]
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.
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