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材料导报  2025, Vol. 39 Issue (14): 23080054-13    https://doi.org/10.11896/cldb.23080054
  高分子与聚合物基复合材料 |
基于新型有机-无机杂化材料的忆阻器在人工突触与神经形态计算领域的应用研究进展
施纯言1, 张程1,*, 毕冉1, 李毅翔1, 何瑞钰1, 袁俊尉2, 李阳1,*
1 苏州科技大学物理科学与技术学院,江苏省微纳热流技术与能源应用重点实验室,江苏 苏州 215009
2 苏州科技大学化学与生命科学学院,江苏 苏州 215009
Research Advances in Emerging Organic-Inorganic Hybrid Memristive Materials for Artificial Synapse and Neuromorphic Computing Applications
SHI Chunyan1, ZHANG Cheng1,*, BI Ran1, LI Yixiang1, HE Ruiyu1, YUAN Junwei2, LI Yang1,*
1 Jiangsu Key Laboratory of Micro and Nano Heat Fluid Flow Technology and Energy Application, School of Physical Science and Technology, Suzhou University of Science and Technology, Suzhou 215009, Jiangsu, China
2 School of Chemistry and Life Sciences, Suzhou University of Science and Technology,Suzhou 215009, Jiangsu, China
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摘要 为解决后摩尔时代的算力瓶颈,基于忆阻器开发高性能的类脑计算受到科研和产业界的追捧。然而,如何实现兼具鲁棒性与低功耗的柔性多态忆阻器和人工突触器件成为当前的研究重点。近年来,新型有机-无机杂化信息材料体系(如低维碳量子点、二维MXenes、金属有机框架、钙钛矿等)已被成功应用于忆阻器和光电突触领域,并在神经形态计算方面表现出巨大发展潜力。本文围绕上述具有代表性的新兴有机-无机杂化忆阻材料,概括性地介绍该类材料体系的发展历程,系统性地总结有机-无机杂化忆阻器的基本概念、器件架构、构效关系、工作原理、后端应用以及当前面临的挑战,拓宽了新型有机-无机杂化忆材料和器件未来研究的深度、广度和维度,为推进集成化仿生感知系统、低能耗量子计算和脑机交互等前沿领域的发展奠定理论基础。
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施纯言
张程
毕冉
李毅翔
何瑞钰
袁俊尉
李阳
关键词:  有机-无机杂化材料  忆阻器  人工突触  神经形态计算    
Abstract: Memristor-based neuromorphic computing has been sought both in academia and industry, due to its promise to solve the computational bottleneck in the post-Moore era. Realizing brain-inspired memristors and artificial synaptic devices with robust stability and low power consumption has become a significant research topic now. In recent years, organic-inorganic hybrid materials, such as Carbon dots, MXenes, Me-tal-organic frameworks, Perovskites, etc. have emerged as potential candidates for optoelectronic synapses and neuromorphic computing applications. Herein, this summary demonstrates the development of four representative organic-inorganic hybrid memristive materials, systematically concludes the memristor concept, device architecture, structure-property relationship, working mechanism, prospective applications, and urgent challenges. This work is anticipated to enhance the comprehension of the integrated memristor device, low-energy quantum computing, brain-computer interaction and more complex human sensory perceptual system.
Key words:  organic-inorganic hybrid materials    memristor    artificial synapse    neuromorphic computing
出版日期:  2025-07-25      发布日期:  2025-07-29
ZTFLH:  O69  
基金资助: 国家自然科学基金(22008164;62304148);江苏省自然科学基金(BK20190939);合成与生物胶体教育部重点实验室(1042050205225990/007);江苏省高等学校自然科学基金(19KJB150018;22KJB150037);苏州市前瞻计划( SYG202351)
通讯作者:  * 张程,苏州科技大学物理科学与技术学院副教授。主要研究方向为有机半导体、二维功能材料设计与合成,以及在忆阻器和人工突触领域的应用。zhangcheng@usts.edu.cn
李阳,苏州科技大学物理科学与技术学院副教授。主要研究方向:(1)有机半导体材料的设计与柔性电子应用研究;(2)新型低维光电材料的构建与低功耗忆阻器的开发;(3)仿生突触器件的集成与类脑神经形态计算的探索。liyang@usts.edu.cn   
作者简介:  施纯言,现为苏州科技大学物理科学与技术学院研究生,师从李阳副教授。目前主要研究领域为有机-无机杂化半导体材料在忆阻器和人工突触领域的应用。
引用本文:    
施纯言, 张程, 毕冉, 李毅翔, 何瑞钰, 袁俊尉, 李阳. 基于新型有机-无机杂化材料的忆阻器在人工突触与神经形态计算领域的应用研究进展[J]. 材料导报, 2025, 39(14): 23080054-13.
SHI Chunyan, ZHANG Cheng, BI Ran, LI Yixiang, HE Ruiyu, YUAN Junwei, LI Yang. Research Advances in Emerging Organic-Inorganic Hybrid Memristive Materials for Artificial Synapse and Neuromorphic Computing Applications. Materials Reports, 2025, 39(14): 23080054-13.
链接本文:  
https://www.mater-rep.com/CN/10.11896/cldb.23080054  或          https://www.mater-rep.com/CN/Y2025/V39/I14/23080054
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