Abstract
Physically unclonable functions (PUFs) are critical security primitives used in authentication and cryptographic key generation. Among these, structural color-based PUFs offer distinct advantages, including fade resistance and the ability to conceal multi-dimensional information. However, current fabrication methods rely heavily on wet processes and laser ablation. Consequently, there is a significant need for flexible PUF labels capable of being produced through a facile and dry process. Here, we present stress-relief modulated photonic crystal PUF labels designed for multi-level dynamic encryption. We achieve random patterning of nanograting-based photonic crystals by leveraging curved pinning edge-induced interruptions and the uncontrolled bulking of the polymeric elastomer due to the uneven adhesion force from the tape. Using artificial intelligence-based deep learning algorithms, we authenticate the labels by extracting structural color, brightness, and saturation, which are determined by the grating periodicity, depth, and orderliness of each pixel. Furthermore, we integrated these photonic crystal patterns with dynamically modulated optical erasure to extend encryption capacity from the spatial to the temporal dimension. We anticipate this approach will enable advanced wearable anti-counterfeiting labels and multi-level digital encryption systems.