神经形态工程学
记忆电阻器
材料科学
峰值时间相关塑性
冯·诺依曼建筑
终端(电信)
可扩展性
计算机科学
光电子学
电阻随机存取存储器
人工神经网络
纳米技术
人工智能
电子工程
长时程增强
电压
电气工程
工程类
受体
操作系统
数据库
化学
电信
生物化学
作者
Lin Wang,Wugang Liao,Swee Liang Wong,Zhi Gen Yu,Sifan Li,Yee‐Fun Lim,Xuewei Feng,Wee Chong Tan,Xin Huang,Li Chen,Liang Liu,Jingsheng Chen,Xiao Gong,Chunxiang Zhu,Xinke Liu,Yong‐Wei Zhang,Dongzhi Chi,Kah‐Wee Ang
标识
DOI:10.1002/adfm.201901106
摘要
Abstract Neuromorphic computing, which emulates the biological neural systems could overcome the high‐power consumption issue of conventional von‐Neumann computing. State‐of‐the‐art artificial synapses made of two‐terminal memristors, however, show variability in filament formation and limited capacity due to their inherent single presynaptic input design. Here, a memtransistor‐based artificial synapse is realized by integrating a memristor and selector transistor into a multiterminal device using monolayer polycrys‐talline‐MoS 2 grown by a scalable chemical vapor deposition (CVD) process. Notably, the memtransistor offers both drain‐ and gate‐tunable nonvolatile memory functions, which efficiently emulates the long‐term potentiation/depression, spike‐amplitude, and spike‐timing‐dependent plasticity of biological synapses. Moreover, the gate tunability function that is not achievable in two‐terminal memristors, enables significant bipolar resistive states switching up to four orders‐of‐magnitude and high cycling endurance. First‐principles calculations reveal a new resistive switching mechanism driven by the diffusion of double sulfur vacancy perpendicular to the MoS 2 grain boundary, leading to a conducting switching path without the need for a filament forming process. The seamless integration of multiterminal memtransistors may offer another degree‐of‐freedom to tune the synaptic plasticity by a third gate terminal for enabling complex neuromorphic learning.
科研通智能强力驱动
Strongly Powered by AbleSci AI