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Vacancy‐Induced Synaptic Behavior in 2D WS2 Nanosheet–Based Memristor for Low‐Power Neuromorphic Computing
Authors:Xiaobing Yan  Qianlong Zhao  Andy Paul Chen  Jianhui Zhao  Zhenyu Zhou  Jingjuan Wang  Hong Wang  Lei Zhang  Xiaoyan Li  Zuoao Xiao  Kaiyang Wang  Cuiya Qin  Gong Wang  Yifei Pei  Hui Li  Deliang Ren  Jingsheng Chen  Qi Liu
Abstract:Memristors with nonvolatile memory characteristics have been expected to open a new era for neuromorphic computing and digital logic. However, existing memristor devices based on oxygen vacancy or metal‐ion conductive filament mechanisms generally have large operating currents, which are difficult to meet low‐power consumption requirements. Therefore, it is very necessary to develop new materials to realize memristor devices that are different from the mechanisms of oxygen vacancy or metal‐ion conductive filaments to realize low‐power operation. Herein, high‐performance and low‐power consumption memristors based on 2D WS2 with 2H phase are demonstrated, which show fast ON (OFF) switching times of 13 ns (14 ns), low program current of 1 µA in the ON state, and SET (RESET) energy reaching the level of femtojoules. Moreover, the memristor can mimic basic biological synaptic functions. Importantly, it is proposed that the generation of sulfur and tungsten vacancies and electron hopping between vacancies are dominantly responsible for the resistance switching performance. Density functional theory calculations show that the defect states formed by sulfur and tungsten vacancies are at deep levels, which prevent charge leakage and facilitate the realization of low‐power consumption for neuromorphic computing application.
Keywords:2D materials  density functional theory calculations  low‐power  memristors  vacancies  WS2 nanosheets
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