Low-dimensional optoelectronic memristors: From quantum confinement to neuromorphic vision

IF 31.6 1区 材料科学 Q1 MATERIALS SCIENCE, MULTIDISCIPLINARY
Yifei Pei , Jiaming Zhang , Mengya Guo , Jianhui Zhao , Liyu Wang , Jisiqi Chen , Xiaobing Yan
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引用次数: 0

Abstract

The von Neumann architecture's inherent separation of memory and computation has become a critical bottleneck in the era of big data, driving the search for integrated computing-memory solutions. Memristors, with their intrinsic ability to unify storage and processing, have emerged as a transformative platform. The exceptional physical properties of low-dimensional materials have played a critical role in this progress, enabling unprecedented device miniaturization, increased storage density, and tunable optoelectronic functionality through their outstanding electronic, optical, and quantum characteristics. This review explores the pivotal role of low-dimensional materials in revolutionizing optoelectronic memristors, focusing on their quantum confinement effects, tunable optoelectronic properties, and neuromorphic applications. We systematically analyze how 0D quantum dots enable light-modulated conductive pathways through precise carrier trapping, 1D nanowires leverage anisotropic charge transport for ultrafast photoresponse, and 2D materials facilitate heterostructure engineering to enhance switching stability. We then deeply analyze the transformative impact of optoelectronic memristors based on low-dimensional materials in neuromorphic computing, particularly their remarkable advantages in simulating complex synaptic dynamics and developing low-energy artificial vision systems. Finally, we specifically outline future research directions, focusing on overcoming bottlenecks in the precise synthesis and scalable fabrication of low-dimensional materials, and leveraging their exceptional optoelectronic properties and tunable quantum characteristics to emulate more intricate synaptic dynamics, thereby bridging the gap between electronic and biological systems. These efforts aim to amplify the role of optoelectronic memristors in future neuromorphic computing and highly integrated chip applications.
低维光电忆阻器:从量子约束到神经形态视觉
冯·诺伊曼架构固有的内存和计算分离已经成为大数据时代的一个关键瓶颈,推动了对计算-内存集成解决方案的探索。忆阻器具有统一存储和处理的内在能力,已经成为一个变革的平台。低维材料的特殊物理特性在这一进程中发挥了关键作用,通过其出色的电子、光学和量子特性,实现了前所未有的器件小型化、存储密度的增加和可调谐的光电功能。本文综述了低维材料在光电子忆阻器革命中的关键作用,重点介绍了它们的量子约束效应、可调谐光电子特性和神经形态应用。我们系统地分析了0D量子点如何通过精确的载流子捕获实现光调制导电通路,1D纳米线如何利用各向异性电荷输运实现超快光响应,以及2D材料如何促进异质结构工程以增强开关稳定性。然后,我们深入分析了基于低维材料的光电忆阻器在神经形态计算中的变革性影响,特别是它们在模拟复杂突触动力学和开发低能量人工视觉系统方面的显着优势。最后,我们特别概述了未来的研究方向,重点是克服低维材料精确合成和可扩展制造的瓶颈,并利用其卓越的光电特性和可调量子特性来模拟更复杂的突触动力学,从而弥合电子和生物系统之间的差距。这些努力旨在扩大光电忆阻器在未来神经形态计算和高度集成芯片应用中的作用。
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来源期刊
Materials Science and Engineering: R: Reports
Materials Science and Engineering: R: Reports 工程技术-材料科学:综合
CiteScore
60.50
自引率
0.30%
发文量
19
审稿时长
34 days
期刊介绍: Materials Science & Engineering R: Reports is a journal that covers a wide range of topics in the field of materials science and engineering. It publishes both experimental and theoretical research papers, providing background information and critical assessments on various topics. The journal aims to publish high-quality and novel research papers and reviews. The subject areas covered by the journal include Materials Science (General), Electronic Materials, Optical Materials, and Magnetic Materials. In addition to regular issues, the journal also publishes special issues on key themes in the field of materials science, including Energy Materials, Materials for Health, Materials Discovery, Innovation for High Value Manufacturing, and Sustainable Materials development.
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