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Demonstrates enhanced anti-counterfeiting in labels using structural color and AI, highlighting security improvement.
Potent anti-counterfeiting technology should be highly secure and easy to identify. However, many existing anti-counterfeiting technologies, such as watermarks and holograms, can be reproduced through high-precision scanning.In general, these methods provide only one-way information transmission, and the anti-counterfeiting mode is restricted. This paper proposes a new strategy to address these limitations by combining structural color, fluorescent color, and AI recognition to create an unclonable fluorescent-responsive, photonic-crystals-based (PCs-based) three-mode anti-counterfeiting label. The structural color patterns of photonic crystals (PCs) constructed by spraying serve as the first level of anti-counterfeiting; the fluorescent response combined with structural color serve as the second level; and the AI recognition of randomly distributed fluorescent dots provide the third level. Rhodamine B (RhB) is a low-cost fluorescent material that can be prepared on a large scale, and the core-shell structured SiO2 @RhB@SiO2 antiparticles (NPs) exhibit excellent abrasion resistance, high-temperature tolerance, and stable physicochemical properties, and can be reused for multiple authentication cycles. A mixture of SiO2 NPs and fluorescent SiO2@RhB@SiO2 NPs was sprayed onto hydrophobic photo paper to from patterns. The randomly distributed fluorescent dots give the labels their unclonable properties. Finally, a database was set up through AI deep learning to identify and authenticate labels with inherent randomness. This study integrates physical and optical characteristics with digital encryption to form multilevel anti-counterfeiting measures, thereby enhancing security. This approach shows great potential in areas such as electronic labels, banknotes, and packaging.
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Jing et al. (2026) studied this question.
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