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Get Free AccessSignificant effort has been devoted to the research of aggregation-induced emission (AIE); however, the discovery of new AIE materials is driven mainly by laborious trial-and-error. In this study, taking triphenylamine (TPA)-based luminophores as an example, we propose an efficient machine-learning scheme for predicting AIE-activity based on quantum mechanics.
Jia Qiu, Kun Wang, Zhouyang Lian, Xing Yang, Wenhui Huang, Anjun Qin, Qian Wang, Jie Tian, Ben Zhong Tang, Shuixing Zhang (2018). Prediction and understanding of AIE effect by quantum mechanics-aided machine-learning algorithm. , 54(57), DOI: https://doi.org/10.1039/c8cc02850h.
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Type
Article
Year
2018
Authors
10
Datasets
0
Total Files
0
Language
en
DOI
https://doi.org/10.1039/c8cc02850h
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