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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. Jaehyun Kang & Taeyoon Kim & Suman Hu & Jaewook Kim & Joon Young Kwak & Jongkil Park & Jong Keuk Park & Inho Kim & Suyoun Lee & Sangbum Kim & YeonJoo Jeong, 2022. "Cluster-type analogue memristor by engineering redox dynamics for high-performance neuromorphic computing," Nature Communications, Nature, vol. 13(1), pages 1-10, December.
    2. Sreetosh Goswami & Rajib Pramanick & Abhijeet Patra & Santi Prasad Rath & Martin Foltin & A. Ariando & Damien Thompson & T. Venkatesan & Sreebrata Goswami & R. Stanley Williams, 2021. "Decision trees within a molecular memristor," Nature, Nature, vol. 597(7874), pages 51-56, September.
    3. Xinge Yu & Zhaoqian Xie & Yang Yu & Jungyup Lee & Abraham Vazquez-Guardado & Haiwen Luan & Jasper Ruban & Xin Ning & Aadeel Akhtar & Dengfeng Li & Bowen Ji & Yiming Liu & Rujie Sun & Jingyue Cao & Qin, 2019. "Skin-integrated wireless haptic interfaces for virtual and augmented reality," Nature, Nature, vol. 575(7783), pages 473-479, November.
    4. Marc H. Garner & Haixing Li & Yan Chen & Timothy A. Su & Zhichun Shangguan & Daniel W. Paley & Taifeng Liu & Fay Ng & Hexing Li & Shengxiong Xiao & Colin Nuckolls & Latha Venkataraman & Gemma C. Solom, 2018. "Comprehensive suppression of single-molecule conductance using destructive σ-interference," Nature, Nature, vol. 558(7710), pages 415-419, June.
    5. Lei Zhang & Chen Yang & Chenxi Lu & Xingxing Li & Yilin Guo & Jianning Zhang & Jinglong Lin & Zhizhou Li & Chuancheng Jia & Jinlong Yang & K. N. Houk & Fanyang Mo & Xuefeng Guo, 2022. "Precise electrical gating of the single-molecule Mizoroki-Heck reaction," Nature Communications, Nature, vol. 13(1), pages 1-11, December.
    6. Tianda Fu & Xiaomeng Liu & Hongyan Gao & Joy E. Ward & Xiaorong Liu & Bing Yin & Zhongrui Wang & Ye Zhuo & David J. F. Walker & J. Joshua Yang & Jianhan Chen & Derek R. Lovley & Jun Yao, 2020. "Bioinspired bio-voltage memristors," Nature Communications, Nature, vol. 11(1), pages 1-10, December.
    7. Bin Zhang & Fei Fan & Wuhong Xue & Gang Liu & Yubin Fu & Xiaodong Zhuang & Xiao-Hong Xu & Junwei Gu & Run-Wei Li & Yu Chen, 2019. "Redox gated polymer memristive processing memory unit," Nature Communications, Nature, vol. 10(1), pages 1-11, December.
    8. Peng Yao & Huaqiang Wu & Bin Gao & Jianshi Tang & Qingtian Zhang & Wenqiang Zhang & J. Joshua Yang & He Qian, 2020. "Fully hardware-implemented memristor convolutional neural network," Nature, Nature, vol. 577(7792), pages 641-646, January.
    9. Zhengwu Liu & Jianshi Tang & Bin Gao & Peng Yao & Xinyi Li & Dingkun Liu & Ying Zhou & He Qian & Bo Hong & Huaqiang Wu, 2020. "Neural signal analysis with memristor arrays towards high-efficiency brain–machine interfaces," Nature Communications, Nature, vol. 11(1), pages 1-9, December.
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