Xiaojuan Lian,Jinke Fu,Zhixuan Gao,Shi‐Pu Gu,Lei Wang
出处
期刊:Chinese Physics B [IOP Publishing] 日期:2022-04-14卷期号:32 (1): 017304-017304被引量:8
标识
DOI:10.1088/1674-1056/ac673f
摘要
Threshold switching (TS) memristors can be used as artificial neurons in neuromorphic systems due to their continuous conductance modulation, scalable and energy-efficient properties. In this paper, we propose a low power artificial neuron based on the Ag/MXene/GST/Pt device with excellent TS characteristics, including a low set voltage (0.38 V) and current (200 nA), an extremely steep slope (< 0.1 mV/dec), and a relatively large off/on ratio (> 10 3 ). Besides, the characteristics of integrate and fire neurons that are indispensable for spiking neural networks have been experimentally demonstrated. Finally, its memristive mechanism is interpreted through the first-principles calculation depending on the electrochemical metallization effect.