An ultrasmall organic synapse for neuromorphic computing

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, Ruoyu Zhang (), Zhang Zhang (), Peng Zhou () and Gang Liu ()
Additional contact information
Shuzhi Liu: 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

Nature Communications, 2023, vol. 14, issue 1, 1-10

Abstract: 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.

Date: 2023
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DOI: 10.1038/s41467-023-43542-2

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