Threshold Switching Memristor Based on 2D SnSe for Nociceptive and Leaky-Integrate and Fire Neuron Simulation

被引:7
|
作者
Qin, Yuwei [1 ]
Wu, Mengfan [1 ]
Yu, Niannian [1 ]
Chen, Ziqi [2 ]
Yuan, Junhui [1 ]
Wang, Jiafu [1 ]
机构
[1] Wuhan Univ Sci & Technol, Sch Sci, Wuhan 430070, Peoples R China
[2] Jianghan Univ, Sch Artificial Intelligence, Wuhan 430056, Peoples R China
基金
中国国家自然科学基金;
关键词
2D material; threshold switching; stochasticLIF neuron; nociceptor; spike neuron network; ENERGY; MODEL;
D O I
10.1021/acsaelm.4c00482
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
Multifunctional neuromorphic devices to tackle complex tasks are highly desirable for the development of artificial neural networks. Threshold switching (TS) memory, which exhibits volatile abrupt resistance change under external electric fields, is capable of emulating multiple biological behaviors because of its rich temporal dynamics. Here, a TS device based on two-dimensional (2D) SnSe is demonstrated. Owing to the diffusive dynamics of Ag ions in SnSe, intrinsic stochasticity of the TS behavior is observed, which can be exploited to construct a compact stochastic Leaky-Integrate and Fire (LIF) model with improved performance in spiking neuron network (SNN). Moreover, an artificial nociceptor is constructed based on the 2D TS device, successfully emulating typical nociceptive features of "threshold", "relaxation", "no adaptation", "hyperalgesia" and "allodynia". The realization of bioinspired devices with combined sensory and information processing abilities paves the way for developing neuromorphic electronics for SNN and humanoid robots.
引用
收藏
页码:4939 / 4947
页数:9
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