A dual-mode transparent device for 360° quasi-omnidirectional self-driven photodetection and efficient ultralow-power neuromorphic computing

Min Jiang; Yukun Zhao; Tong Liu; Yanyan Chang; Yuan Tang; Min Zhou; Yiping Shi; Jianya Zhang; Lifeng Bian; Shulong Lu

doi:10.1038/s41377-025-01991-y

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A dual-mode transparent device for 360° quasi-omnidirectional self-driven photodetection and efficient ultralow-power neuromorphic computing

Original Articles

- A dual-mode transparent device for 360° quasi-omnidirectional self-driven photodetection and efficient ultralow-power neuromorphic computing
- Light: Science & Applications Vol. 14, Issue 10, Pages: 2936-2954(2025)
- Affiliations：
  
  1.School of Nano-Tech and Nano-Bionics, University of Science and Technology of China (USTC), Hefei 230026, China
  2.Division of Nano-Devices Research, Suzhou Institute of Nano-Tech and Nano-Bionics (SINANO), Chinese Academy of Sciences (CAS), Suzhou 215123, China
  3.Key Laboratory of Semiconductor Display Materials and Chips, SINANO, CAS, Suzhou 215123, China
  4.Vacuum Interconnected Nanotech Workstation, SINANO, CAS, Suzhou 215123, China
  5.Key Laboratory of Intelligent Optoelectronic Devices and Chips of Jiangsu Higher Education Institutions, School of Physical Science and Technology, Suzhou University of Science and Technology, Suzhou 215009, China
  6.Frontier Institute of Chip and System, Fudan University, Shanghai 200433, China
- Author bio：
  
  Yukun Zhao (ykzhao2017@sinano.ac.cn)
  Jianya Zhang (jyzhang2022@usts.edu.cn)
  Lifeng Bian (lfbian@fudan.edu.cn)
  Shulong Lu (sllu2008@sinano.ac.cn)
- Funds：
- DOI：10.1038/s41377-025-01991-y
  CLC：
- Received：24 January 2025，
  
  Revised：2025-07-17，
  
  Accepted：25 July 2025，
  
  Published Online：12 August 2025，
  
  Published：31 October 2025
- Accepted：
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Jiang, M. et al. A dual-mode transparent device for 360° quasi-omnidirectional self-driven photodetection and efficient ultralow-power neuromorphic computing. Light: Science & Applications, 14, 2936-2954 (2025).
DOI：

Jiang, M. et al. A dual-mode transparent device for 360° quasi-omnidirectional self-driven photodetection and efficient ultralow-power neuromorphic computing. Light: Science & Applications, 14, 2936-2954 (2025). DOI： 10.1038/s41377-025-01991-y.

摘要

Abstract

Due to the extremely high manufacturing standards

the integration of quasi-omnidirectional photodetectors and synaptic devices within a single device remains a long-standing challenge. In this work

we have designed a graphene/(Al

Ga)N nanowire heterojunction

demonstrating the monolithic integration of self-driven 360° photodetectors and artificial synapses in a dual-mode transparent device successfully. By manipulating the carrier transport dynamics through controlling the bias voltage

the degree of oxygen vacancy ionization can be precisely regulated

ultimately realizing the monolithic dual-mode device. At 0 V bias

the device functions as a fast-response self-driven photodetector with

stable optical communication capabilities

achieving 360° quasi-omnidirectional photodetection. Upon applying a bias voltage

the operating mode switches to a synaptic device

which successfully simulates brain-like paired-pulse facilitation

short-/long-term plasticity processes

and learning/forgetting behaviors. The device demonstrates an exceptionally high UV/visible rejection ratio of 1.29 × 10

coupled with an ultra-low dark current of less than 1 pA. Furthermore

this device has a low power consumption of 2.5 × 10

−14

J per synaptic event

indicating an energy efficiency comparable to synaptic processes in the human brain. Moreover

nonlinear photoconductivity lets the device become a neuromorphic sensor for preprocessing images

enhancing recognition accuracy. Importantly

by leveraging the long-memory characteristic of the devices in open-circuit voltage mode

the devices have been successfully applied to guide humanoid robots in performing direction distinguishing and motion learning. This work provides new insights into the integrated manufacturing of multifunctional monolithic devices and foresees their immense potential in upcoming advanced

low-power neuromorphic computing systems.

关键词

Keywords

references

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