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An ultrasmall organic synapse for neuromorphic computing

Author

Listed:
  • Shuzhi Liu

    (Shanghai Jiao Tong University
    Shanghai Jiao Tong University)

  • Jianmin Zeng

    (Shanghai Jiao Tong University)

  • Zhixin Wu

    (Shanghai Jiao Tong University)

  • Han Hu

    (Chinese Academy of Sciences)

  • Ao Xu

    (Hefei University of Technology)

  • Xiaohe Huang

    (Fudan University)

  • Weilin Chen

    (Shanghai Jiao Tong University)

  • Qilai Chen

    (Sun Yat-Sen University)

  • Zhe Yu

    (Sun Yat-Sen University)

  • Yinyu Zhao

    (Chinese Academy of Sciences)

  • Rong Wang

    (Chinese Academy of Sciences)

  • Tingting Han

    (Hefei University of Technology)

  • Chao Li

    (Hefei University of Technology)

  • Pingqi Gao

    (Sun Yat-Sen University)

  • Hyunwoo Kim

    (Hankyong National University)

  • Seung Jae Baik

    (Hankyong National University)

  • Ruoyu Zhang

    (Chinese Academy of Sciences)

  • Zhang Zhang

    (Hefei University of Technology)

  • Peng Zhou

    (Fudan University)

  • Gang Liu

    (Shanghai Jiao Tong University)

Abstract

High‐performance organic neuromorphic devices with miniaturized device size and computing capability are essential elements for developing brain‐inspired humanoid intelligence technique. However, due to the structural inhomogeneity of most organic materials, downscaling of such devices to nanoscale and their high‐density integration into compact matrices with reliable device performance remain challenging at the moment. Herein, based on the design of a semicrystalline polymer PBFCL10 with ordered structure to regulate dense and uniform formation of conductive nanofilaments, we realize an organic synapse with the smallest device dimension of 50 nm and highest integration size of 1 Kb reported thus far. The as‐fabricated PBFCL10 synapses can switch between 32 conductance states linearly with a high cycle‐to‐cycle uniformity of 98.89% and device‐to‐device uniformity of 99.71%, which are the best results of organic devices. A mixed-signal neuromorphic hardware system based on the organic neuromatrix and FPGA controller is implemented to execute spiking‐plasticity‐related algorithm for decision-making tasks.

Suggested Citation

  • Shuzhi Liu & Jianmin Zeng & Zhixin Wu & Han Hu & Ao Xu & Xiaohe Huang & Weilin Chen & Qilai Chen & Zhe Yu & Yinyu Zhao & Rong Wang & Tingting Han & Chao Li & Pingqi Gao & Hyunwoo Kim & Seung Jae Baik , 2023. "An ultrasmall organic synapse for neuromorphic computing," Nature Communications, Nature, vol. 14(1), pages 1-10, December.
  • Handle: RePEc:nat:natcom:v:14:y:2023:i:1:d:10.1038_s41467-023-43542-2
    DOI: 10.1038/s41467-023-43542-2
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    1. Pengshan Xie & Yunchao Xu & Jingwen Wang & Dengji Li & Yuxuan Zhang & Zixin Zeng & Boxiang Gao & Quan Quan & Bowen Li & You Meng & Weijun Wang & Yezhan Li & Yan Yan & Yi Shen & Jia Sun & Johnny C. Ho, 2024. "Birdlike broadband neuromorphic visual sensor arrays for fusion imaging," Nature Communications, Nature, vol. 15(1), pages 1-12, December.

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