Unclonable MXene Topographies as Robust Anti-Counterfeiting Tags via Fast Laser Scanning and Siamese Neural Networks

Abstract

An ideal anti-counterfeiting technology is desired to be unclonable, nondestructive, mass-producible, and accompanied with fast and robust authentication under various external influences. Although multiple anti-counterfeiting technologies have been reported, few meet all of the above-mentioned features. Herein, a mechanically driven patterning process is reported to produce higher dimensional Ti3C2Tx MXene topographies in a scalable yet unclonable manner, which can be used as anti-counterfeiting tags. By using a high-speed confocal laser microscopy, the complex topographies can be extracted within one minute and then reconstructed into 3D physical unclonable function (PUF) keys. Meanwhile, a Siamese neural network model and a feature-tracking software are built to achieve a pick-and-check strategy, enabling highly accurate, robust, disturbance-insensitive tag authentication in practical exploitations. The 3D PUF key-based anti-counterfeiting technology features with several advances, including ultrahigh encoding capacities (≈10144 000-107 800 000), fast processing times (<1 min), and high authentication accuracy under various external disturbances, including tag rotations (≈0°‒360°), tag dislocation(s) in x(y) directions (≈0%‒100%), tag shifts in z-direction (≈0%‒28%), tag tilts (≈0°‒5°), differences in contrasts (20%‒60%) and laser power (6.0‒9.0 µW). The anti-counterfeiting technology promises information security, encoding capacity, and authentication efficiency for the manufacturer-distributor-customer distribution processes.