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

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 ar...

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Veröffentlicht in:IEEE electron device letters 2019-10, Vol.40 (10), p.1686-1689
Hauptverfasser: Chen, Yihao, Wang, Yu, Luo, Yuhao, Liu, Xinwei, Wang, Yuqi, Gao, Fei, Xu, Jianguang, Hu, Ertao, Samanta, Subhranu, Wan, Xiang, Lian, Xiaojuan, Xiao, Jian, Tong, Yi
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Sprache:eng
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Zusammenfassung: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.
ISSN:0741-3106
1558-0563
DOI:10.1109/LED.2019.2936261