A facile photonics reconfigurable memristor with dynamically allocated neurons and synapses functions

Zhenyu Zhou; Lulu Wang; Gongjie Liu; Yuchen Li; Zhiyuan Guan; Zixuan Zhang; Pengfei Li; Yifei Pei; Jianhui Zhao; Jiameng Sun; Yahong Wang; Yiduo Shao; Xiaobing Yan

doi:10.1038/s41377-025-01928-5

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A facile photonics reconfigurable memristor with dynamically allocated neurons and synapses functions

Original Articles

- A facile photonics reconfigurable memristor with dynamically allocated neurons and synapses functions
- Light: Science & Applications Vol. 14, Issue 10, Pages: 2904-2914(2025)
- Affiliations：
  
  1.Key Laboratory of Brain-Like Neuromorphic Devices and Systems of Hebei Province, College of Electron and Information Engineering, School of Life Sciences, Institute of Life Science and Green Development, Hebei University, Baoding, China
  2.School of Electronic Science and Engineering, Xiamen University, Xiamen 361005, China
- Author bio：
  
  Xiaobing Yan (yanxiaobing@ime.ac.cn)
- Funds：
- DOI：10.1038/s41377-025-01928-5
  CLC：
- Received：04 February 2025，
  
  Revised：2025-05-15，
  
  Accepted：19 June 2025，
  
  Published Online：12 August 2025，
  
  Published：31 October 2025
- Accepted：
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Zhou, Z. Y. et al. A facile photonics reconfigurable memristor with dynamically allocated neurons and synapses functions. Light: Science & Applications, 14, 2904-2914 (2025).
DOI：

Zhou, Z. Y. et al. A facile photonics reconfigurable memristor with dynamically allocated neurons and synapses functions. Light: Science & Applications, 14, 2904-2914 (2025). DOI： 10.1038/s41377-025-01928-5.

摘要

Abstract

The dynamic neural network function realized by reconfigurable memristors to implement artificial neurons and synapses is an effective method to complete the next generation of neuromorphic computing. However

due to the limitation of reconfiguration conditions

there are inconsistencies in the turn-on voltage and operating current before and after the reconfiguration of neuromorphic devices

which leads to huge difficulties in hardware application development and is an urgent problem to be solved. In this work

we introduced light as a regulatory means in the memristor and achieved the reconfiguration of volatile (endurance ~10

cycles) and non-volatile (retention ~10

s) characteristics with a unified working parameter through the photoelectric coupling mode. The switching voltage of the device can be controlled 100% by this method without any limiting current. This will allow neurons and synapses to be dynamically allocated on demand. We completed the verification such as Morse code decoding

Poisson coded image recognition

denoising in the image recognition process

and intelligent traffic signal recognition hardware system under different work modes. It is verified that the device can dynamically adjust the neuromorphic according to needs

providing a new idea for the further integration of neuromorphic computing in the future.

关键词

Keywords

references

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