Two-dimensional van der Waals ferroelectrics: A pathway to next-generation devices in memory and neuromorphic computing

被引:2
|
作者
Zhao, Hongyuan [1 ,2 ]
Yun, Jiangni [2 ]
Li, Zhen [1 ,3 ]
Liu, Yu [1 ,3 ]
Zheng, Lei [1 ,3 ]
Kang, Peng [1 ,2 ,3 ]
机构
[1] Tianmushan Lab, Hangzhou 311115, Peoples R China
[2] Northwest Univ, Sch Informat Sci & Technol, Xian 710127, Peoples R China
[3] Beihang Univ, Sch Mat Sci & Engn, Beijing 100191, Peoples R China
基金
中国国家自然科学基金;
关键词
Von Neumann systems; 2D Ferroelectric materials; Si-CMOS technology; Non-volatile memories; Neural network computing; FIELD-EFFECT TRANSISTORS; TUNNEL-JUNCTIONS; RECTIFICATION; MANIPULATION; ELECTRONICS; CAPACITORS; SYNAPSES; INPLANE; DRIVEN; ARRAYS;
D O I
10.1016/j.mser.2024.100873
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
The rapid increase in CPU processing speeds has significantly advanced artificial intelligence, yet it has also exacerbated the disparity in CPU utilization and data throughput rates due to the shared memory architecture of traditional von Neumann systems. To enhance computational efficiency, there is a critical need to explore advanced functional materials and integrate these into novel computing architectures. Two-dimensional (2D) ferroelectric materials, characterized by their atomic-scale ferroelectric non-volatile properties and low switching barriers, emerge as promising candidates. These materials are particularly suitable for use as nonvolatile resistors and artificial synapses within in-memory computing frameworks. Furthermore, their compatibility with Si-CMOS technology enables the high-density integration of devices, potentially driving a new paradigm in integrated computation between processing units and storage architectures. This review focuses on recent developments in 2D ferroelectric materials, including their structural properties, polarization switching mechanisms, and diverse applications. Special emphasis is placed on their potential in integrated applications such as non-volatile memories, neural network computing, non-volatile logic operations, and optoelectronic memories within neuromorphic computing devices.
引用
收藏
页数:28
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