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Touch-modulated van der Waals heterostructure with self-writing power switch for synaptic simulation

  • Caifang Gao
  • , Qianfan Nie
  • , Che Yi Lin
  • , Fanming Huang
  • , Liangjun Wang
  • , Wei Xia
  • , Xiang Wang
  • , Zhigao Hu
  • , Mengjiao Li
  • , Hong Wei Lu
  • , Ying Chih Lai*
  • , Yen Fu Lin*
  • , Junhao Chu
  • , Wenwu Li*
  • *此作品的通讯作者
  • East China Normal University
  • Fudan University
  • National Chung Hsing University

科研成果: 期刊稿件文章同行评审

摘要

Neuromorphic electronics with two-dimensional van der Waals materials meet the ever-increasing demands of both the semiconductor industry and biological engineering, such as miniaturization, structure flexibility, multifunctionality, and low power consumption. However, the majority of reported electronic devices achieve multifarious memory storage states or synaptic plasticity through regulation of an electrical or an optical signal. Herein, we propose an innovative touch-modulated device based on an indium selenide/hexagonal boron nitride/graphene van der Waals heterostructure coupled with a triboelectric nanogenerator. The device is prepared utilizing a simple copper grid shadow mask instead of the expensive and cumbersome electron beam lithography process, exhibits high mobility of 829 cm2 V−1 s−1, low voltage, and low power consumption. Nonvolatile memory with self-writing power, durability and multibit data storage is achieved through mechanical modulation without an additional gate-voltage supply. Moreover, by adjusting the distance between the two friction layers, essential synaptic plasticity, including short-term and long-term potentiation/depression and paired-pulse facilitation/depression, are successfully imitated in the device. Most importantly, we achieve ultralow power consumption of 165 aJ in tribotronic synapses owing to the ultra-high mobility of InSe. Our tribotronic synapse with self-writing power has great potential to simulate the low-power-consuming neuromorphic bioelectronic devices with multiple functions and lays the foundation for future advanced neuromorphic systems and artificial intelligence.

源语言英语
文章编号106659
期刊Nano Energy
91
DOI
出版状态已出版 - 1月 2022
已对外发布

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    可持续发展目标 7 经济适用的清洁能源

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