Exploiting deep learning for predictable carbon dot design

Chem Commun (Camb). 2021 Jan 14;57(4):532-535. doi: 10.1039/d0cc07882d. Epub 2020 Dec 18.

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.