You, Kejia, Lin, Jiasong, Wang, Zhen, Jiang, Yi, Sun, Jiayu, Lin, Qinghong, Hu, Xin, Fu, Hongyang, Guo, Xuan, Zhao, Yi, Lin, Liangxu, Liu, Yang, and Li, Fushan
Anticounterfeiting technologies meet challenges in the Internet of Things era due to the rapidly growing volume of objects, their frequent connection with humans, and the accelerated advance of counterfeiting/cracking techniques. Here, we, inspired by biological fingerprints, present a simple anticounterfeiting system based on perovskite quantum dot (PQD) fingerprint physical unclonable function (FPUF) by cooperatively utilizing the spontaneous-phase separation of polymers and selective in situ synthesis PQDs as an entropy source. The FPUFs offer red, green, and blue full-color fingerprint identifiers and random three-dimensional (3D) morphology, which extends binary to multivalued encoding by tuning the perovskite and polymer components, enabling a high encoding capacity (about 108570000, far surpassing that of biometric fingerprints). The strategy is compatible with mainstream production techniques that are widely used in traditional low-cost printed anticounterfeiting labels including spray printing, stamping, writing, and laser printing, avoiding complicated fabrication. Macrographical patterns and micro/nanofingerprint patterns with multiscale-tailorable inter-ridge sizes can be fused into a single FPUF label, satisfying different levels of anticounterfeiting requirements. Furthermore, a smart fused scheme of enhanced deep learning and fingerprint characteristic comparison is leveraged, by which high-efficiency, high-accuracy authentication of our FPUFs is achieved even for the increasingly huge FPUF databases and imperfectly captured images from users.