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Smart phosphor with neuromorphic behaviors enabling full-photoluminescent Write and Read for all-optical physical reservoir computing

Author

Listed:
  • Yifei Zhao

    (The Hong Kong Polytechnic University)

  • Man Li

    (South China University of Technology)

  • Man Chung Wong

    (The Hong Kong Polytechnic University)

  • Xun Han

    (The Hong Kong Polytechnic University)

  • Feng Guo

    (The Hong Kong Polytechnic University
    The Hong Kong Polytechnic University Shenzhen Research Institute)

  • Yuan Liu

    (The Hong Kong Polytechnic University)

  • Xinyue Lao

    (The Hong Kong Polytechnic University)

  • Zhaoying Dang

    (The Hong Kong Polytechnic University
    The Hong Kong Polytechnic University Shenzhen Research Institute)

  • Sin-Yi Pang

    (The Hong Kong Polytechnic University)

  • Zehan Wu

    (The Hong Kong Polytechnic University)

  • Shi Ye

    (South China University of Technology)

  • Jianhua Hao

    (The Hong Kong Polytechnic University
    The Hong Kong Polytechnic University Shenzhen Research Institute
    The Hong Kong Polytechnic University)

Abstract

The unprecedented growth in information across diverse media drives an urgent need for multifunctional materials and devices beyond conventional electrical paradigms. This work explores all-optical information processing based on photoluminescence functions using smart phosphor. The developed composite phosphor of mixed-halide perovskite embedded macroporous Y2O3:Eu3+ exhibits adaptive photoluminescence variations with neuromorphic characteristics. Theoretical simulations reveal interface-mediated halogen migration processes with progressively evolving energy barriers, underpinning the neuron-like photoluminescence property variations. The system enables full photoluminescence-based Write and Read functionalities for all-optical neuromorphic computing, achieving 4-bit binary sequence discrimination as physical reservoirs. It further demonstrates potential in photoluminescence-based fingerprint authentication with 94.4% accuracy. This work advances smart phosphor as an alternative approach to neuromorphic computing with optical-stimuli and optical-output. It also opens avenues for designing function-oriented phosphor materials with tailored properties for information science and artificial intelligence applications.

Suggested Citation

  • Yifei Zhao & Man Li & Man Chung Wong & Xun Han & Feng Guo & Yuan Liu & Xinyue Lao & Zhaoying Dang & Sin-Yi Pang & Zehan Wu & Shi Ye & Jianhua Hao, 2025. "Smart phosphor with neuromorphic behaviors enabling full-photoluminescent Write and Read for all-optical physical reservoir computing," Nature Communications, Nature, vol. 16(1), pages 1-11, December.
  • Handle: RePEc:nat:natcom:v:16:y:2025:i:1:d:10.1038_s41467-025-62745-3
    DOI: 10.1038/s41467-025-62745-3
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