Laser Fabrication of Multi‐Dimensional Perovskite Patterns with Intelligent Anti‐Counterfeiting Applications
Abstract Perovskites have gained widespread attention across various fields such as photovoltaics, displays, and imaging. Despite their promising applications, achieving precise and high‐quality patterning of perovskite films remains a challenge. In this study, femtosecond laser direct writing techn...
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| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2024-11-01
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| Series: | Advanced Science |
| Subjects: | |
| Online Access: | https://doi.org/10.1002/advs.202309862 |
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| Summary: | Abstract Perovskites have gained widespread attention across various fields such as photovoltaics, displays, and imaging. Despite their promising applications, achieving precise and high‐quality patterning of perovskite films remains a challenge. In this study, femtosecond laser direct writing technology is utilized to achieve rapid and highly precise micro/nanofabrication on perovskites. The study successfully fabricates multiple structured and emission‐tunable perovskite patterns composed of A2(FA)n−1PbnX3n+1 (A represents a series of long‐chain amine cations, and X = Cl, Br, I), encompassing 2D, quasi‐2D, and 3D structures. The study delves into the intricate interplay between fabrication technology and the growth of multi‐dimensional perovskites: higher repetition rates, coupled with appropriate laser power, prove more conducive to perovskite growth. By employing precise halogen element design, the simultaneous generation of two distinct color quick‐response (QR) code patterns is achieved through one‐step laser processing. These mirrored QR codes offer a novel approach to anti‐counterfeiting. To further enhance anti‐counterfeiting capabilities, artificial intelligence (AI)‐based methods are introduced for recognizing patterned perovskite anti‐counterfeiting labels. The combination of deep learning algorithms and a non‐deterministic manufacturing process provides a convenient means of identification and creates unclonable features. This integration of materials science, laser fabrication, and AI offers innovative solutions for the future of security features. |
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| ISSN: | 2198-3844 |