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Research Article

Realize ultralow-energy-consumption photo-synaptic device based on a single (Al,Ga)N nanowire for neuromorphic computing

Xiushuo Gu1,2,§, Min Zhou2,3,§, Yukun Zhao2,3( ), Qianyi Zhang1,2, Jianya Zhang4, Yonglin Huang1( ), Shulong Lu2,3
College of Electronic and Optical Engineering & College of Flexible Electronics (Future Technology), Nanjing University of Posts and Telecommunications, Nanjing 210023, China
Key Lab of Nanodevices and Applications, Suzhou Institute of Nano-Tech and Nano-Bionics (SINANO), Chinese Academy of Sciences (CAS), Suzhou 215123, China
School of Nano-Tech and Nano-Bionics, University of Science and Technology of China, Hefei 230026, China
Jiangsu Key Laboratory of Micro and Nano Heat Fluid Flow Technology and Energy Application, School of Physical Science and Technology, Suzhou University of Science and Technology, Suzhou 215009, China

§ Xiushuo Gu and Min Zhou contributed equally to this work.

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Graphical Abstract

It is pretty novel to demonstrate a light-stimulated synaptic device based on a single (Al,Ga)N nanowire successfully, which can mimic the multiple functions of biological synapses under the stimulation of both 310 and 365 nm photons. The energy consumption of the synaptic device can be reduced to 5.58 × 10−13 J, which is close to that of biological synapses in the human brain. Thanks to the advantage of ultralow energy consumption, this work shows great potential in promoting the development of brain-inspired systems and high-level integrated neuromorphic computing.

Abstract

The rapid development of artificial intelligence poses an urgent need for low-energy-consumption and small-sized artificial photonic synapses. Here, it is pretty novel to demonstrate a light-stimulated synaptic device based on a single (Al,Ga)N nanowire successfully. Thanks to the presence of vacancy defects in the single nanowire, the artificial synaptic device can simulate multiple functions of biological synapses under stimulation of both 310 and 365 nm light photons, including paired-pulse facilitation, spike timing dependent plasticity, and memory learning capabilities. The energy consumption of artificial synaptic device can be reduced as little as 5.58 × 10−13 J, which is close to that of the biological synapse in human brain. Furthermore, the synaptic device is demonstrated to have the high stability for both long-time stimulation and long-time storage. Based on the experimental conductance of long-term potentiation and long-term depression, the simulated three-layer neural network can achieve a high recognition rate of 92% after only 10 training epochs. With a brain-like behavior, the single-nanowire-based synaptic devices can promote the development of visual neuromorphic computing technology and artificial intelligence systems requiring ultralow energy consumption.

Keywords

single (Al,Ga)N nanowirelight-stimulated synaptic devicelow-energy-consumptionneural network

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Nano Research
Volume 17 Issue 3,
March 2024
Pages 1933-1941
DOI: 10.1007/s12274-023-6069-0
Cite this article:
Gu X, Zhou M, Zhao Y, et al. Realize ultralow-energy-consumption photo-synaptic device based on a single (Al,Ga)N nanowire for neuromorphic computing. Nano Research, 2024, 17(3): 1933-1941. https://doi.org/10.1007/s12274-023-6069-0
Topics:
PhotodetectorsWide band gap semiconductors

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Received: 02 June 2023
Revised: 28 July 2023
Accepted: 07 August 2023
Published: 31 August 2023
© Tsinghua University Press 2023
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