记忆电阻器
材料科学
神经形态工程学
冯·诺依曼建筑
灵活性(工程)
人工神经网络
纳米技术
计算机科学
数码产品
电子工程
计算机体系结构
人工智能
电气工程
工程类
统计
数学
操作系统
作者
Kai Tang,Yang Wang,Chuanhui Gong,Chujun Yin,Miao Zhang,Xianfu Wang,Jie Xiong
标识
DOI:10.1002/aelm.202101099
摘要
Abstract Next‐generation memristive devices and neuromorphic computing have many fantastic properties in breaking down the memory walls of conventional von Neumann structures. Electronic and photoelectronic memristors are the most important basic components, equipping with the capability of data storage and information processing for electronic and photoelectronic signals. 2D layered materials exhibit many unique physical advantages such as novel mechanisms, ultrathin channel, high mechanical flexibility, and easy electrical control, and thus demonstrate great potential for memory with high density, fast speed, and low power consumption. In recent years, abundant and fruitful designs have been devoted in terms of 2D memristors. Herein, the recent advances of 2D electronic and photoelectronic memristors are reviewed, as well as the application on simulating artificial brain neural network and visual neural network, respectively. An overview of the challenges and perspectives on the exploitation of 2D materials for memristors is given, and routes to realize practical brain and visual neural network are proposed.
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