Self‐Powered Luminescent Barcode Recognition System Based on Triboelectric‐Induced Electroluminescence

Abstract Information identification systems hold critical significance in personal authentication and Internet of Things (IoT) applications. This paper proposes a novel self‐powered luminescent barcode system based on sliding‐mode triboelectric‐induced electroluminescence, where mechanical motion is directly converted into visual light signals through in situ triboelectrification processes. The system achieves controllable modulation of emission intensity by leveraging material‐dependent triboelectric polarization differences. After incorporating lead zirconate titanate with a high dielectric constant to enhance interfacial electric fields, the system demonstrates significantly improved luminescence intensity, enabling effective identification of dynamic optical patterns generated by random sliding motions. A barcode recognition system constructed on the C# platform enables real‐time translation of optical information into digital codes, achieving rapid response within 0.2 s through optimized recognition algorithms. This work enables direct decoding of barcode optical signals via WeChat Mini Programs on smartphones, eliminating the reliance on specialized decoding equipment. The developed barcode card exhibits high concealment, electromagnetic interference resistance, and cycling stability exceeding 20 000 cycles. With self‐powered luminescent characteristics, non‐invasive recognition mode, and reusability advantages, this system presents promising potential for IoT device authentication and personal information security applications.

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Publication Details

Journal
Advanced Materials Technologies
Published
2025-09-02
DOI
https://doi.org/10.1002/admt.202500968
Primary Topic
Advanced Sensor and Energy Harvesting Materials
Type
article
Field-Weighted Citation Impact
0.00

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article

Self‐Powered Luminescent Barcode Recognition System Based on Triboelectric‐Induced Electroluminescence

Hui Yu, Wei Peng, Zheng Jie Tan
Advanced Materials Technologies
Advanced Sensor and Energy Harvesting Materials
article

Self‐Powered Luminescent Barcode Recognition System Based on Triboelectric‐Induced Electroluminescence

Hui Yu, Wei Peng, Zheng Jie Tan
article en

Abstract

Abstract Information identification systems hold critical significance in personal authentication and Internet of Things (IoT) applications. This paper proposes a novel self‐powered luminescent barcode system based on sliding‐mode triboelectric‐induced electroluminescence, where mechanical motion is directly converted into visual light signals through in situ triboelectrification processes. The system achieves controllable modulation of emission intensity by leveraging material‐dependent triboelectric polarization differences. After incorporating lead zirconate titanate with a high dielectric constant to enhance interfacial electric fields, the system demonstrates significantly improved luminescence intensity, enabling effective identification of dynamic optical patterns generated by random sliding motions. A barcode recognition system constructed on the C# platform enables real‐time translation of optical information into digital codes, achieving rapid response within 0.2 s through optimized recognition algorithms. This work enables direct decoding of barcode optical signals via WeChat Mini Programs on smartphones, eliminating the reliance on specialized decoding equipment. The developed barcode card exhibits high concealment, electromagnetic interference resistance, and cycling stability exceeding 20 000 cycles. With self‐powered luminescent characteristics, non‐invasive recognition mode, and reusability advantages, this system presents promising potential for IoT device authentication and personal information security applications.

Advanced Materials TechnologiesVol. 10(24)
Dalian University of Technology (CN), Dalian University (CN)
National Natural Science Foundation of China, National Key Research and Development Program of China, Fundamental Research Funds for the Central Universities
Openalex Percentile: Top 78%
Advanced Sensor and Energy Harvesting Materials
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