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

Yifei Zhao, Man Li, Man Chung Wong, Xun Han, Feng Guo, Yuan Liu, Xinyue Lao, Zhaoying Dang, Sin-Yi Pang, Zehan Wu, Shi Ye () and Jianhua Hao ()
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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
Yuan Liu: The Hong Kong Polytechnic University
Xinyue Lao: The Hong Kong Polytechnic University
Zhaoying Dang: The Hong Kong Polytechnic University
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

Nature Communications, 2025, vol. 16, issue 1, 1-11

Abstract: 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.

Date: 2025
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DOI: 10.1038/s41467-025-62745-3

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