神经形态工程学
记忆电阻器
材料科学
钴
低能
能源消耗
光电子学
纳米技术
计算机体系结构
计算机科学
电子工程
电气工程
物理
工程类
人工智能
冶金
人工神经网络
原子物理学
作者
Yun Ji,Baoshan Tang,Jinyong Wang,Haofei Zheng,Zhengjin Weng,Yangwu Wu,Sifan Li,Aaron Thean,Kah‐Wee Ang
出处
期刊:ACS Nano
[American Chemical Society]
日期:2024-12-31
被引量:4
标识
DOI:10.1021/acsnano.4c11890
摘要
Two-dimensional (2D) materials hold significant potential for the development of neuromorphic computing architectures owing to their exceptional electrical tunability, mechanical flexibility, and compatibility with heterointegration. However, the practical implementation of 2D memristors in neuromorphic computing is often hindered by the challenges of simultaneously achieving low latency and low energy consumption. Here, we demonstrate memristors based on 2D cobalt phosphorus trisulfide (CoPS
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