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

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.

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Publication Details

Journal
Advanced Functional Materials
Published
2026-01-19
DOI
https://doi.org/10.1002/adfm.202529742
Primary Topic
Physical Unclonable Functions (PUFs) and Hardware Security
Type
article
Field-Weighted Citation Impact
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article

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

Yong Chen, Enguo Chen, Wenzong Lai, Yun Ye et al.
Advanced Functional Materials
Physical Unclonable Functions (PUFs) and Hardware Security
article

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

Yong Chen, Enguo Chen, Wenzong Lai, Yun Ye, Sheng Xu, Tailiang Guo, Junhu Cai, Huilong Yang, Zheng Zhou
article en

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.

Advanced Functional Materials
Tan Kah Kee Innovation Laboratory (CN), Fuzhou University (CN)
Openalex Percentile: Top 90%
Physical Unclonable Functions (PUFs) and Hardware Security
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