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Mechanoplastic Tribotronic Floating-Gate Neuromorphic Transistor

  • Xixi Yang
  • , Jinran Yu
  • , Jing Zhao
  • , Youhui Chen
  • , Guoyun Gao
  • , Yifei Wang
  • , Qijun Sun*
  • , Zhong Lin Wang*
  • *此作品的通讯作者
  • Chinese Academy of Sciences
  • University of Chinese Academy of Sciences
  • National Center for Nanoscience and Technology
  • Guangxi University
  • Georgia Institute of Technology

科研成果: 期刊稿件文章同行评审

摘要

The emulation of synaptic plasticity to achieve sophisticated cognitive functions and adaptive behaviors is critical to the evolution of neuromorphic computation and artificial intelligence. More feasible plastic strategies (e.g., mechanoplasticity) are urgent to achieve comparable, versatile, and active cognitive complexity in neuromorphic systems. Here, a versatile mechanoplastic artificial synapse based on tribotronic floating-gate MoS2 synaptic transistors is proposed. Mechanical displacement can induce triboelectric potential coupling to the floating-gate synaptic transistor, trigger a postsynaptic current signal, and modulate the synaptic weights, which realizes the synaptic mechanoplasticity in an active and interactive way. Typical synaptic plasticity behaviors including potentiation/inhibition and paired pulse facilitation/depression are successfully imitated. Assistant with the charge trapping by floating gate, the artificial synapse can realize mechanical displacement derived short-term and long-term plasticity simultaneously. A facile artificial neural network is also constructed to demonstrate an adding synaptic weight and neuromorphic logic switching (AND, OR) by mechanoplasticity without building complex complementary metal oxide semiconductor circuits. The proposed mechanoplastic artificial synapse offers a favorable candidate for the construction of mechanical behavior derived neuromorphic devices to overcome the von Neumann bottleneck and perform advanced synaptic behaviors.

源语言英语
期刊论文编号2002506
期刊Advanced Functional Materials
30
34
DOI
出版状态已出版 - 1 8月 2020

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