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基于二维材料的忆阻器技术在神经形态计算方面的最新进展。

Recent Advancements in 2D Material-Based Memristor Technology Toward Neuromorphic Computing.

作者信息

Park Sungmin, Naqi Muhammad, Lee Namgyu, Park Suyoung, Hong Seongin, Lee Byeong Hyeon

机构信息

Department of Physics, Gachon University, Seongnam 13120, Republic of Korea.

Department of Electronic Engineering, University of Exeter, Exeter EX4 4QF, UK.

出版信息

Micromachines (Basel). 2024 Nov 29;15(12):1451. doi: 10.3390/mi15121451.

Abstract

Two-dimensional (2D) layered materials have recently gained significant attention and have been extensively studied for their potential applications in neuromorphic computing, where they are used to mimic the functions of the human brain. Their unique properties, including atomic-level thickness, exceptional mechanical stability, and tunable optical and electrical characteristics, make them highly versatile for a wide range of applications. In this review, we offer a comprehensive analysis of 2D material-based memristors. Furthermore, we examine the ability of 2D material-based memristors to successfully mimic the human brain by referencing their neuromorphic applications.

摘要

二维(2D)层状材料近来备受关注,并因其在神经形态计算中的潜在应用而得到广泛研究,在神经形态计算中它们被用于模拟人类大脑的功能。它们的独特性质,包括原子级厚度、出色的机械稳定性以及可调节的光学和电学特性,使其在广泛的应用中具有高度通用性。在本综述中,我们对基于二维材料的忆阻器进行了全面分析。此外,我们通过参考其神经形态应用来研究基于二维材料的忆阻器成功模拟人类大脑的能力。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7f61/11676942/78feaa7f75b4/micromachines-15-01451-g001.jpg

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