Frontiers in Computational Neuroscience (Sep 2022)

Real-time numerical system convertor via two-dimensional WS2-based memristive device

  • Xing Xin,
  • Liyao Sun,
  • Jiamei Chen,
  • Youzhe Bao,
  • Ye Tao,
  • Ya Lin,
  • Jingyao Bian,
  • Zhongqiang Wang,
  • Xiaoning Zhao,
  • Haiyang Xu,
  • Yichun Liu

DOI
https://doi.org/10.3389/fncom.2022.1015945
Journal volume & issue
Vol. 16

Abstract

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The intriguing properties of two-dimensional (2D) transition metal dichalcogenides (TMDCs) enable the exploration of new electronic device architectures, particularly the emerging memristive devices for in-memory computing applications. Implementation of arithmetic logic operations taking advantage of the non-linear characteristics of memristor can significantly improve the energy efficiency and simplify the complexity of peripheral circuits. Herein, we demonstrate an arithmetic logic unit function using a lateral volatile memristor based on layered 2D tungsten disulfide (WS2) materials and some combinational logic circuits. Removable oxygen ions were introduced into WS2 materials through oxygen plasma treatment process. The resistive switching of the memristive device caused by the thermophoresis-assisted oxygen ions migration has also been revealed. Based on the characteristics of excitatory postsynaptic current (EPSC), paired-pulse facilitation (PPF), and spike rate dependent plasticity (SRDP), a real-time numerical system convertor was successfully accomplished, which is a significant computing function of arithmetic logic unit. This work paves a new way for developing 2D memristive devices for future arithmetic logic applications.

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