Litcius/Paper detail

Unclonable Anti‐Counterfeiting Labels Based on Plasmonic‐Patterned Nanostructures

Zilun Tang, Xiaopeng Liu, Xiaochun Liu, Jianyu Wu, Wenjing Lin, Xiaofeng Lin, Guobin Yi

2022Advanced Engineering Materials39 citationsDOI

Abstract

Herein this study, plasmonic‐patterned nanostructures are applied to fabricate unclonable anti‐counterfeiting labels. Patterned Au nanoparticles (AuNPs) are constructed by the skillful combination of diblock copolymer polystyrene‐block‐poly(4‐vinyl pyridine) (PS‐ b ‐P4VP) self‐assembly with shadow mask lithography to provide a simple and universal approach for large‐area fabrication of patterned nanostructures. The AuNP pattern can be made visible by increasing the nanoparticle size. A surface‐enhanced Raman spectroscopy (SERS) ‐ based physical unclonable function (PUF) security label with a large encoding capacity is fabricated by depositing malachite green (MG) on the surface. The broadening of the size distribution of the AuNPs after their growth and the increased disorder in their arrangement confer the security label with unique and unclonable characteristics. The as‐prepared optical PUF security label is read out by a confocal Raman spectrometer to extract binary codes, which are then authenticated through comparison. These SERS‐based PUF security labels, which combine patterning with stochastic spectral encoding, not only provide rich and diverse patterns but are also promising for anti‐counterfeiting applications in areas such as rigid silicon‐based optoelectronic materials and devices.

Topics & Concepts

Materials sciencePhysical unclonable functionNanotechnologySurface-enhanced Raman spectroscopyRaman spectroscopyPolystyrenePlasmonNanostructureLithographyNanoparticleFabricationOptoelectronicsRaman scatteringComputer scienceCryptographyOpticsPolymerPathologyPhysicsMedicineAlternative medicineComputer securityComposite materialPhysical Unclonable Functions (PUFs) and Hardware SecurityGold and Silver Nanoparticles Synthesis and ApplicationsAdvanced Memory and Neural Computing