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Physical unclonable functions (PUFs) have emerged as a promising encryption technology, utilizing intrinsic physical identifiers that offer enhanced security and tamper resistance. Multi‐level PUFs boost system complexity, thereby improving system reliability and fault tolerance. However, crosstalk‐free multi‐level PUFs remain a persistent challenge. In this study, a hierarchical PUF system that harnesses the spontaneous phase separation of silk fibroin /PVA blend and the random distribution of silicon‐vacancy diamonds within the blend is presented. The thermodynamic instability of phase separation and inherent unpredictability of diamond dispersion gives rise to intricate random patterns at two distinct scales, enabling time‐efficient hierarchical authentication for cryptographic keys. These patterns are complementary yet independent, inherently resistant to replication and damage thus affording robust security and reliability to the proposed system. Furthermore, customized authentication algorithms are constructed: visual PUFs authentication utilizes neural network combined structural similarity index measure, while spectral PUFs authentication employs Hamming distance and cross‐correlation bit operation. This hierarchical PUF system attains a high recognition rate without interscale crosstalk. Additionally, the coding capacity is exponentially enhanced using M‐ary encoding to reinforce multi‐level encryption. Hierarchical PUFs hold significant potential for immediate application, offering unprecedented data protection and cryptographic key authentication capabilities. [ABSTRACT FROM AUTHOR]

Mechanoluminescence (ML) is a fascinating phenomenon with diverse applications in pressure sensing, damage detection, and stress distribution visualization. However, most ML materials exhibit instantaneous photon emission that requires real‐time recording with a photodetector, and thereby circumscribing their applicability predominantly to real‐time stress‐sensing scenarios. In this work, a novel method is introduced for non‐real‐time stress sensing utilizing Li0.1Na0.9NbO3:Pr3+ phosphor, which allows for the retrieval of pressure location and intensity even 20 days after the event. The influence of heat and pressure on the trap depth distribution is analyzed using thermoluminescence (TL) and ML measurements, and it is proved that both heat and pressure release the captured electrons in the same traps. Leveraging the intricate competition between mechanical and thermal detrapping processes, stress information can be accessed through TL imaging. Furthermore, an algorithm is proposed based on this phenomenon to authenticate the stress information. This research not only advances the fundamental understanding of ML phenomena but also introduces a novel approach for applications such as mechano‐history indicators, security papers, and advanced data storage systems. [ABSTRACT FROM AUTHOR]

As the Internet of Things (IoT) continues its pervasive influence and digital technologies increasingly weave into the fabric of daily lives, the imperative for robust security measures becomes paramount to mitigate the escalating risks to the digital landscape. Traditional anti‐counterfeiting technologies, while capable to some extent, are constrained by factors such as material toxicity, low‐security efficacy, and intricate fabrication process. Mechanoluminescent materials have shown great potential in the areas of anti‐counterfeiting and security. Here, a multicolor mechanoluminescent (ML) material (lanthanide doped Ca2B2O5) synthesized by solid‐phase reaction is reported for the first time at a relatively lower temperature of 750 °C. The ML devices are obtained by embedding ML materials into polydimethylsiloxane elastomer, allowing for stress visualization with colors ranging from blue and green to orange and red. Through elaborate co‐doping, successive and accurate stress visualizations are realized. Finally, security labels based on the lanthanide ions doped Ca2B2O5 are prepared and also demonstrated to safeguard valuable packages. This work provides a novel multicolor ML material and pioneers its use in security labels, offering a universal solution for multicolor display, information security, dynamic anti‐counterfeiting, and other potential applications within the realm of IoT. [ABSTRACT FROM AUTHOR]