Issue 24, 2022

Cracking enabled unclonability in colloidal crystal patterns authenticated with computer vision

Abstract

Colloidal crystals with iridescent structural coloration have appealing applications in the fields of sensors, displays, anti-counterfeiting, etc. A serious issue accompanying the facile chemical self-assembly approach to colloidal crystals is the formation of uncontrolled and irregular cracks. In contrast to the previous efforts to avoid cracking, the unfavorable and random micro-cracks in colloidal crystals were utilized here as unclonable codes for tamper-proof anti-counterfeiting. The special structural and optical characteristics of the colloidal crystal patterns assembled with monodisperse poly(styrene-methyl methacrylate-acrylic acid) core–shell nanospheres enabled multi-anti-counterfeiting modes, including angle-dependent structural colors and polarization anisotropy, besides the physically unclonable functions (PUFs) of random micro-cracks. Moreover, by using the random cracks in the colloidal crystals as templates to guide fluorescent silica nanoparticle deposition, an fluorescent anti-counterfeiting mode with PUFs was introduced. To validate the PUFs of the fluorescent micro-cracks in the colloidal crystals, a novel edge-sensitive template matching approach based on a computer vision algorithm with an accuracy of ∼100% was developed, enabling ultimate security immune to forgery. The computer-vision verifiable physically unclonable colloidal crystals with multi-anti-counterfeiting modes are superior to conventional photonic crystal anti-counterfeiting materials that rely on angle-dependent or tunable structural colors, and the conventional PUF labels in the aspect of decorative functions, which will open a new avenue for advanced security materials with multi-functionality.

Graphical abstract: Cracking enabled unclonability in colloidal crystal patterns authenticated with computer vision

Supplementary files

Article information

Article type
Paper
Submitted
17 mar 2022
Accepted
17 may 2022
First published
17 may 2022

Nanoscale, 2022,14, 8833-8841

Cracking enabled unclonability in colloidal crystal patterns authenticated with computer vision

Y. Li, Y. Mao, J. Wang, Z. Liu, P. Jia, N. Wu, H. Yu, J. Wang, Y. Song and J. Zhou, Nanoscale, 2022, 14, 8833 DOI: 10.1039/D2NR01479C

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