Inkjet-printed unclonable quantum dot fluorescent anti-counterfeiting labels with artificial intelligence authentication

Yang Liu, Fei Han, Fushan Li (), Yan Zhao, Maosheng Chen, Zhongwei Xu, Xin Zheng, Hailong Hu, Jianmin Yao, Tailiang Guo, Wanzhen Lin, Yuanhui Zheng (), Baogui You, Pai Liu, Yang Li and Lei Qian ()
Additional contact information
Yang Liu: Fuzhou University
Fei Han: Fuzhou University
Fushan Li: Fuzhou University
Yan Zhao: Fuzhou University
Maosheng Chen: Fuzhou University
Zhongwei Xu: Fuzhou University
Xin Zheng: Fuzhou University
Hailong Hu: Fuzhou University
Jianmin Yao: Fuzhou University
Tailiang Guo: Fuzhou University
Wanzhen Lin: Fuzhou University
Yuanhui Zheng: Fuzhou University
Baogui You: Guangdong Poly Optoelectronics Co., Ltd
Pai Liu: Guangdong Poly Optoelectronics Co., Ltd
Yang Li: Guangdong Poly Optoelectronics Co., Ltd
Lei Qian: TCL Corporate Research

Nature Communications, 2019, vol. 10, issue 1, 1-9

Abstract: Abstract An ideal anti-counterfeiting technique has to be inexpensive, mass-producible, nondestructive, unclonable and convenient for authentication. Although many anti-counterfeiting technologies have been developed, very few of them fulfill all the above requirements. Here we report a non-destructive, inkjet-printable, artificial intelligence (AI)-decodable and unclonable security label. The stochastic pinning points at the three-phase contact line of the ink droplets is crucial for the successful inkjet printing of the unclonable security labels. Upon the solvent evaporation, the three-phase contact lines are pinned around the pinning points, where the quantum dots in the ink droplets deposited on, forming physically unclonable flower-like patterns. By utilizing the RGB emission quantum dots, full-color fluorescence security labels can be produced. A convenient and reliable AI-based authentication strategy is developed, allowing for the fast authentication of the covert, unclonable flower-like dot patterns with different sharpness, brightness, rotations, amplifications and the mixture of these parameters.

Date: 2019
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DOI: 10.1038/s41467-019-10406-7

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