神经形态工程学
材料科学
铁电性
记忆电阻器
横杆开关
光电子学
二极管
冯·诺依曼建筑
计算机科学
电子工程
人工神经网络
工程类
电介质
人工智能
操作系统
作者
Bochang Li,Sifan Li,Han Wang,Li Chen,Liang Liu,Xuewei Feng,Yesheng Li,Jingsheng Chen,Xiao Gong,Kah‐Wee Ang
标识
DOI:10.1002/aelm.202000760
摘要
Abstract Memristors with biological synaptic behaviors and functions have been intensively studied as an important component for neuromorphic computing system, which hold promise to address the power consumption issue in modern computers based on von Neumann architecture. However, the resistive switching mechanism that relies on the stochastic formation of conductive filaments leads to poor cycle‐to‐cycle (temporal) and cell‐to‐cell (spatial) variations for filamentary memristors. The emergence of memristors based on 2D ferroelectric materials can potentially avoid these issues. Here, a vertical Au/CuInP 2 S 6 (CIPS)/Ti diode is demonstrated using exfoliated ferroelectric CIPS flake. Through ferroelectric switching, the CIPS diode realizes resistive switching with a ratio larger than 6 × 10 3 . The endurance measurement shows a small set and reset voltage variation of 5.3% and 9.1%, respectively. Key synaptic behaviors including spike‐time‐dependent plasticity, paired‐pulse‐facilitation, and paired‐pulse‐depression are successfully mimicked, manifesting the potential application of CIPS diode in a neuromorphic computing system. Moreover, pattern learning and memory behaviors are emulated using a 3 × 3 CIPS crossbar array.
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