Suppr超能文献

用于神经形态计算的超小型有机突触。

An ultrasmall organic synapse for neuromorphic computing.

作者信息

Liu Shuzhi, Zeng Jianmin, Wu Zhixin, Hu Han, Xu Ao, Huang Xiaohe, Chen Weilin, Chen Qilai, Yu Zhe, Zhao Yinyu, Wang Rong, Han Tingting, Li Chao, Gao Pingqi, Kim Hyunwoo, Baik Seung Jae, Zhang Ruoyu, Zhang Zhang, Zhou Peng, Liu Gang

机构信息

Department of Micro/Nano Electronics, School of Electronic Information and Electrical Engineering, Shanghai Jiao Tong University, Shanghai, 200240, China.

School of Chemistry and Chemical Engineering, Shanghai Jiao Tong University, Shanghai, 200240, China.

出版信息

Nat Commun. 2023 Nov 23;14(1):7655. doi: 10.1038/s41467-023-43542-2.

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 PBFCL 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 PBFCL 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.

摘要

具有小型化器件尺寸和计算能力的高性能有机神经形态器件是开发受大脑启发的类人智能技术的关键要素。然而,由于大多数有机材料的结构不均匀性,目前将此类器件缩小至纳米尺度并将其高密度集成到具有可靠器件性能的紧凑矩阵中仍然具有挑战性。在此,基于具有有序结构的半结晶聚合物PBFCL的设计来调节导电纳米丝的致密和均匀形成,我们实现了一种有机突触,其器件尺寸最小为50 nm,集成规模最大为1 Kb,是迄今为止报道的最好结果。所制备的PBFCL突触能够在32个电导状态之间线性切换,具有98.89%的高循环间均匀性和99.71%的器件间均匀性,这是有机器件的最佳结果。基于有机神经矩阵和FPGA控制器实现了一个混合信号神经形态硬件系统,以执行与脉冲可塑性相关的算法用于决策任务。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9c97/10667342/8b4489e9d4f4/41467_2023_43542_Fig1_HTML.jpg

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