神经形态工程学
材料科学
计算机体系结构
非易失性存储器
计算机科学
纳米技术
光电子学
人工智能
人工神经网络
作者
Yan Li,Guanglong Ding,Yongbiao Zhai,Ziyu Lv,Yan Yan,Shuangmei Xue,Kui Zhou,Meng Zhang,Yutong Zhang,Qijun Sun,Yi Liu,Vellaisamy A. L. Roy,Ye Zhou,Su‐Ting Han
出处
期刊:Small
[Wiley]
日期:2025-01-31
卷期号:: e2410914-e2410914
被引量:23
标识
DOI:10.1002/smll.202410914
摘要
As the age of the Internet of Things (IoTs) unfolds, along with the rapid advancement of artificial intelligence (AI), traditional von Neumann-based computing systems encounter significant challenges in handling vast amounts of data storage and processing. Bioinspired neuromorphic computing strategies offer a promising solution, characterized by features of in-memory computing, massively parallel processing, and event-driven operations. Compared to traditional rigid silicon-based devices, flexible neuromorphic devices are lightweight, thin, and highly stretchable, garnering considerable attention. Among the materials utilized in these devices, transition metal carbides/nitrides (MXenes) are particularly noteworthy materials with their excellent flexibility, exceptional conductivity, and hydrophilicity, which confer remarkable properties upon these devices. Herein, a comprehensive discussion is provided on the applications of MXenes in flexible memory and neuromorphic devices. This review covers the basic principles and device structures of memory and neuromorphic devices, common parameters and emerging materials of flexible devices, as well as the common synthesis, functionalization methods, and distinct properties of MXenes. The remaining challenges and future opportunities of MXenes in relevant devices are also presented. This review can serve as a valuable reference and lay a cornerstone for the practical and feasible implementation of MXenes in flexible memory and neuromorphic technologies.
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