神经形态工程学
黑磷
石墨烯
材料科学
六方氮化硼
纳米技术
异质结
悬空债券
计算机科学
计算机体系结构
工程物理
光电子学
硅
物理
人工神经网络
人工智能
作者
Chenyin Feng,Wen‐Wei Wu,Huidi Liu,Junke Wang,Houzhao Wan,Guokun Ma,Hao Wang
出处
期刊:Nanomaterials
[MDPI AG]
日期:2023-10-07
卷期号:13 (19): 2720-2720
被引量:10
摘要
Recently, two-dimensional (2D) materials and their heterostructures have been recognized as the foundation for future brain-like neuromorphic computing devices. Two-dimensional materials possess unique characteristics such as near-atomic thickness, dangling-bond-free surfaces, and excellent mechanical properties. These features, which traditional electronic materials cannot achieve, hold great promise for high-performance neuromorphic computing devices with the advantages of high energy efficiency and integration density. This article provides a comprehensive overview of various 2D materials, including graphene, transition metal dichalcogenides (TMDs), hexagonal boron nitride (h-BN), and black phosphorus (BP), for neuromorphic computing applications. The potential of these materials in neuromorphic computing is discussed from the perspectives of material properties, growth methods, and device operation principles.
科研通智能强力驱动
Strongly Powered by AbleSci AI