Unclonable MXene Topographies as Robust Anti‐Counterfeiting Tags via Fast Laser Scanning and Siamese Neural Networks (Adv. Mater. Technol. 19/2023)
Source abstract
Abstract
Anti-Counterfeiting Tags High dimensional Ti3C2Tx MXene topographies are generated in a unclonable manner, which can be read with layer-by-layer laser confocal imaging and reconstructed to 3D PUF keys, as demonstrated by Lin Jing, Qian Xie, Po-Yen Chen, and co-workers in article 2300568. Pairing with a pick-and-check strategy and a self-trained Siamese neural network, this anti-counterfeiting technology features ultrahigh encoding capacity, fast processing, and high authentication accuracy under various external disturbances including tag rotations, dislocations, and mechanical/thermal stresses.
Source: openalex_inverted_index · Quality: baseline
Research context
OpenAlex topics: Physical Unclonable Functions (PUFs) and Hardware Security · Integrated Circuits and Semiconductor Failure Analysis · Advanced Memory and Neural Computing
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
Department of Chemical and Biomolecular Engineering National University of Singapore 4 Engineering Drive 4 Singapore 117585 Singapore
School of Metallurgic Engineering Anhui University of Technology 59 Hudong Road Ma'anshan 243002 P.R. China
Department of Chemical and Biomolecular Engineering University of Maryland College Park MD 20740 USA
Maryland Robotics Center College Park MD 20740 USA <?vsp 103pt?>
References
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