神经形态工程学
纳米技术
纳米材料
材料科学
异质结
纳米线
电子线路
记忆电阻器
计算机科学
量子点
计算机体系结构
光电子学
电子工程
人工神经网络
电气工程
工程类
人工智能
作者
Vinod K. Sangwan,Mark C. Hersam
标识
DOI:10.1038/s41565-020-0647-z
摘要
Memristive and nanoionic devices have recently emerged as leading candidates for neuromorphic computing architectures. While top-down fabrication based on conventional bulk materials has enabled many early neuromorphic devices and circuits, bottom-up approaches based on low-dimensional nanomaterials have shown novel device functionality that often better mimics a biological neuron. In addition, the chemical, structural and compositional tunability of low-dimensional nanomaterials coupled with the permutational flexibility enabled by van der Waals heterostructures offers significant opportunities for artificial neural networks. In this Review, we present a critical survey of emerging neuromorphic devices and architectures enabled by quantum dots, metal nanoparticles, polymers, nanotubes, nanowires, two-dimensional layered materials and van der Waals heterojunctions with a particular emphasis on bio-inspired device responses that are uniquely enabled by low-dimensional topology, quantum confinement and interfaces. We also provide a forward-looking perspective on the opportunities and challenges of neuromorphic nanoelectronic materials in comparison with more mature technologies based on traditional bulk electronic materials. This Review highlights the progress made towards the development of neuromorphic devices and architectures enabled by low-dimensional nanomaterials
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