Multispectral Quantum Dot Tags for Advanced Anticounterfeiting Applications

Physical unclonable functions (PUFs) based on nanophotonic materials offer a promising route toward secure and tamper-resistant authentication. Here, we introduce a quantum dots (QDs)-driven optical fingerprinting (identifier) platform that utilizes four distinct photoluminescence (PL) emission peaks generated from two cadmium-free CIS/ZnS QDs formulations deposited side-by-side. Under multiwavelength excitation, each of them exhibits a dual-peak emission response, yielding a combined four-peak, multiexcitation spectral profile. By extracting the wavelength, full width at half-maximum, and intensity from each peak across nine excitation wavelengths, we obtain 108 independent spectral features, which are converted into a 216-bit binary fingerprint. This work incorporates a features fusion strategy that compresses multidimensional spectral descriptors into compact, discriminative digital features, enabling stable, high-entropy encoding from complex PL emission behavior. Comprehensive statistical analysis demonstrates strong uniqueness with a mean inter-Hamming distance of 0.512 ± 0.028, a wide collision margin of 99-123 differing bits, and repeatability with near-zero intra-tag variation. Bit-level randomness metrics confirm near-ideal statistical behavior after binarization. The four-peaks architecture therefore represents a significant advancement over single-peak or dual-peaks luminescent PUFs, enabling dense, high-entropy fingerprints from cadmium-free materials while remaining compatible with typical readout hardware. This work establishes a foundation for next-generation optical authentication technologies using multipeak QDs emitters.

Authors

Institutions

Publication Details

Journal
ACS Applied Nano Materials
Published
2026-04-11
DOI
https://doi.org/10.1021/acsanm.6c00386
Primary Topic
Physical Unclonable Functions (PUFs) and Hardware Security
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Multispectral Quantum Dot Tags for Advanced Anticounterfeiting Applications

Yueyu Guo, K. De Groot, Nema M. Abdelazim, Syeda Ramsha Ali
ACS Applied Nano Materials
Physical Unclonable Functions (PUFs) and Hardware Security
article

Multispectral Quantum Dot Tags for Advanced Anticounterfeiting Applications

Yueyu Guo, K. De Groot, Nema M. Abdelazim, Syeda Ramsha Ali
article en

Abstract

Physical unclonable functions (PUFs) based on nanophotonic materials offer a promising route toward secure and tamper-resistant authentication. Here, we introduce a quantum dots (QDs)-driven optical fingerprinting (identifier) platform that utilizes four distinct photoluminescence (PL) emission peaks generated from two cadmium-free CIS/ZnS QDs formulations deposited side-by-side. Under multiwavelength excitation, each of them exhibits a dual-peak emission response, yielding a combined four-peak, multiexcitation spectral profile. By extracting the wavelength, full width at half-maximum, and intensity from each peak across nine excitation wavelengths, we obtain 108 independent spectral features, which are converted into a 216-bit binary fingerprint. This work incorporates a features fusion strategy that compresses multidimensional spectral descriptors into compact, discriminative digital features, enabling stable, high-entropy encoding from complex PL emission behavior. Comprehensive statistical analysis demonstrates strong uniqueness with a mean inter-Hamming distance of 0.512 ± 0.028, a wide collision margin of 99-123 differing bits, and repeatability with near-zero intra-tag variation. Bit-level randomness metrics confirm near-ideal statistical behavior after binarization. The four-peaks architecture therefore represents a significant advancement over single-peak or dual-peaks luminescent PUFs, enabling dense, high-entropy fingerprints from cadmium-free materials while remaining compatible with typical readout hardware. This work establishes a foundation for next-generation optical authentication technologies using multipeak QDs emitters.

ACS Applied Nano MaterialsVol. 9(16)
University of Southampton (GB)
Electronics and Computer Science, University of Southampton, Engineering and Physical Sciences Research Council
Reduced inequalities
Openalex Percentile: Top 19%
Physical Unclonable Functions (PUFs) and Hardware Security
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.