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.

Anti-counterfeiting technologies should ideally be unclonable, yet simple to fabricate and decode. Here, the authors develop an inkjet-printable and unclonable security label based on random patterning of quantum dot inks, and accompany it with an artificial intelligence decoding mechanism capable of authenticating the patterns.

Details

Title
Inkjet-printed unclonable quantum dot fluorescent anti-counterfeiting labels with artificial intelligence authentication
Author
Liu, Yang 1 ; Han, Fei 2 ; Li Fushan 1 ; Zhao, Yan 1 ; Chen, Maosheng 1 ; Xu, Zhongwei 1 ; Zheng, Xin 1 ; Hu, Hailong 1   VIAFID ORCID Logo  ; Yao Jianmin 1 ; Guo Tailiang 1 ; Lin Wanzhen 2 ; Zheng Yuanhui 2   VIAFID ORCID Logo  ; You Baogui 3 ; Pai, Liu 3 ; Yang, Li 3 ; Qian Lei 4 

 Fuzhou University, Institute of Optoelectronic Technology, Fuzhou, China (GRID:grid.411604.6) (ISNI:0000 0001 0130 6528) 
 Fuzhou University, College of Chemistry, Fuzhou, China (GRID:grid.411604.6) (ISNI:0000 0001 0130 6528) 
 Guangdong Poly Optoelectronics Co., Ltd, Jiangmen, China (GRID:grid.411604.6) 
 TCL Corporate Research, Shenzhen, China (GRID:grid.411604.6) 
Publication year
2019
Publication date
2019
Publisher
Nature Publishing Group
e-ISSN
20411723
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
2233827632
Copyright
© The Author(s) 2019. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.