3D Data Encryption and Random‐Featured Anti‑Counterfeiting Enabled by Single‐Step Grayscale Lithographic Quantum‐Dot Patterns

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Authors: Enguo Chen, Junhu Cai, Wenzong Lai, Huilong Yang, Zheng Zhou, Yun Ye, Sheng Xu, Tailiang Guo, Enguo Chen
Cited by: 4
References: 45

Abstract

ABSTRACT State‐of‐the‐art anti‐counterfeiting technologies are transitioning from planar 2D labels to volumetric 3D architectures. Embedding encrypted data in the labels adds a hidden information dimension accessible only with specific keys or designated readout protocols. However, most reported 3D anti‐counterfeiting patterns are implemented as multi‐layer stacks and lack cryptographic capability, while reliance on specialized equipment further limits scalability and broad adoption. Herein, we propose a synergistic strategy for information encryption and anti‐counterfeiting through integrated encoding and authentication mechanisms. Quantum dot (QD) patterns are created through single‐step grayscale lithography, where encrypted information is directly embedded into the 3D structure. The resulting structure incorporates a randomized physical unclonable function (PUF), conferring inherent and unforgeable uniqueness. Artificial intelligence (AI) is employed for anti‐counterfeiting recognition and authentication, while 3D topography scanning enables accurate decoding and reconstruction of the encrypted information. This approach integrates high design flexibility with rapid patterning, enabling 5 mm × 5 mm 3D QD patterns to be fabricated within 5 min. The patterns are proven to retain fluorescence and authentication accuracy after more than 6 months of storage without additional encapsulation. The method is highly compatible with existing micro/nanolithography processes, paving the way for low‐cost, high‐throughput fabrication of 3D QD structures.

Fields of Study & Subjects

Physical Unclonable Functions (PUFs) and Hardware Security Nanofabrication and Lithography Techniques Chaos-based Image/Signal Encryption

Publication details

Journal / source
Advanced Functional Materials
Publisher
Wiley
Volume
36
Issue
34
Publication date
19 January 2026
Language
EN