Bio‐Inspired Unclonable Anti‐Counterfeiting Based on Random Patterns of Colloidal Crystal Flakes
Jingjiu Song, Lunyuan Zhang, Zhenhua Wang, Pan Jia, Zhiwei Liu, Guofu Zhang, Xin Zhang, Na Wu, Yanlin Song, Jinming ZhouABSTRACT
Inspired by the random, colorful Turing patterns on the wings of the butterfly ( Papilio paris Linnaeus), unclonable anti‐counterfeiting based on interspersed structural colors has been developed by randomly dispersing colloidal crystal flakes (CCFs) into a functional polymeric matrix. The tiny shining CCFs exhibit irregular shapes, random sizes, stochastic distributions, and a rich variety of color hues, which together provide strong visual distinctiveness and high encoding capacity—key attributes for physical unclonable functions (PUFs). The PUF features—uniform bit uniformity, high randomness, and high uniqueness—are verified through both static and dynamic digital encoding. Angle‐dependence and tunable structural colors in response to solvents could provide preliminary anti‐counterfeiting modes, defending against printed replica attacks and allowing PUF labels without relying on high‐resolution. Furthermore, by selecting diverse polymeric matrices, a range of on‐demand functions can be integrated, including excellent mechanical properties, good stability, self‐healing, adhesion, and hydrophobicity, all of which facilitate practical security applications. To assess authentication reliability, deep learning demonstrates high accuracy (up to 100%) with rapid processing time (within seconds). Our approach integrates convenient fabrication, automatic & accurate authentication, and customizable functions, positioning it as a promising solution for advanced anti‐counterfeiting in high‐value goods.