4.6 Article

Realization of Artificial Neuron Using MXene Bi-Directional Threshold Switching Memristors

期刊

IEEE ELECTRON DEVICE LETTERS
卷 40, 期 10, 页码 1686-1689

出版社

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/LED.2019.2936261

关键词

Leaky-integration-and-fire (LIF); MXene; memristor; artificial neuron

资金

  1. National Natural Science Foundation of China [61704088, 61804079, 61874059]
  2. China Postdoctoral Science Foundation [2018M642290]
  3. Postgraduate Research and Practice Innovation Program of Jiangsu Province [SJKY19_0811]
  4. Jiangsu provincial key talent project [SZDG2018007, CZ1060619001, TJ218001]
  5. Science Foundation of Nanjing University of Posts and Telecommunications [NY217116, NY218110, KFJJ20170101]
  6. National and Local Joint Engineering Laboratory of RF Integration and Micro-Assembly Technology, Nanjing University of Posts and Telecommunications
  7. College of Electronic and Optical Engineering, Nanjing University of Posts and Telecommunications
  8. College of Microelectronics, Nanjing University of Posts and Telecommunications

向作者/读者索取更多资源

Artificial neurons and synapses are critical units for processing intricate information in brain-inspired neuromorphic systems. Memristors are frequently engineered as artificial synapses due to their simple structures, nonlinear dynamics, and high-density integration. However, the development of artificial neurons on memristors has less progress. In this letter, we propose a rich dynamics-driven artificial neuron based on two-dimensional materials MXene. Partial essential neural features of neural processing, including leaky integration, automatic threshold-driven fire, and self-recovery, were successfully emulated in a unified manner. The space-charge-limited current (SCLC) model accompanied by electrochemical metallization effect was used to explain electrical characteristics. This work will provide a useful guideline for designing and manipulating memristor as artificial neurons for brain-inspired systems.

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