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

Author

Listed:
  • 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)

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.

Suggested Citation

  • 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 & Lei Qian, 2019. "Inkjet-printed unclonable quantum dot fluorescent anti-counterfeiting labels with artificial intelligence authentication," Nature Communications, Nature, vol. 10(1), pages 1-9, December.
  • Handle: RePEc:nat:natcom:v:10:y:2019:i:1:d:10.1038_s41467-019-10406-7
    DOI: 10.1038/s41467-019-10406-7
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    Cited by:

    1. Xu, Zhongwei & Li, Dianlun & Wang, Kun & Liu, Ye & Wang, Jiaxin & Qiu, Zhirong & Wu, Chaoxing & Lin, Jintang & Guo, Tailiang & Li, Fushan, 2022. "Stomatopod-inspired integrate-and-fire triboelectric nanogenerator for harvesting mechanical energy with ultralow vibration speed," Applied Energy, Elsevier, vol. 312(C).
    2. Junfang Zhang & Rong Tan & Yuxin Liu & Matteo Albino & Weinan Zhang & Molly M. Stevens & Felix F. Loeffler, 2024. "Printed smart devices for anti-counterfeiting allowing precise identification with household equipment," Nature Communications, Nature, vol. 15(1), pages 1-9, December.
    3. Pengwei Xiao & Zhoufan Zhang & Junjun Ge & Yalei Deng & Xufeng Chen & Jian-Rong Zhang & Zhengtao Deng & Yu Kambe & Dmitri V. Talapin & Yuanyuan Wang, 2023. "Surface passivation of intensely luminescent all-inorganic nanocrystals and their direct optical patterning," Nature Communications, Nature, vol. 14(1), pages 1-11, December.
    4. Tongtong Zhang & Lingzhi Wang & Jing Wang & Zhongqiang Wang & Madhav Gupta & Xuyun Guo & Ye Zhu & Yau Chuen Yiu & Tony K. C. Hui & Yan Zhou & Can Li & Dangyuan Lei & Kwai Hei Li & Xinqiang Wang & Qi W, 2023. "Multimodal dynamic and unclonable anti-counterfeiting using robust diamond microparticles on heterogeneous substrate," Nature Communications, Nature, vol. 14(1), pages 1-11, December.

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