Akademik Veri Yönetim Sistemi
Advanced Materials Technologies, 2025 (SCI-Expanded, Scopus)
The security issues imposed by the digital age necessitate the development of multi-level encoding solutions based on deterministic and stochastic layers. This study reports a hybrid encoding approach that combines deterministic patterns fabricated by photolithography with stochastic features formed by solid-state dewetting of silver films under strong confinement at the micrometer and nanometer length scales within and out of plane, respectively. Informed by the understanding of the thickness-dependent solid-state dewetting under spatial confinement, the rational design and fabrication of interfaces enable three-layer encoding. The first deterministic layer, composed of a quick-response (QR) code, can be effectively read out by using a smartphone. The random silver features formed within the QR code form two stochastic layers with bright-field and dark-field microscopy resolvable responses. The localized surface plasmon resonance-mediated scattering in the dark-field enables a multi-color response, ensuring both unclonability and enhanced encoding capacity. The feature and color matching algorithms based on deep learning algorithms directly and rapidly authenticate stochastic features with high verification accuracy in a user-friendly manner. This method offers a promising path toward practical anti-counterfeit technologies by embedding unclonable features using a semiconductor industry-compatible manufacturing process.