神经形态工程学
材料科学
记忆电阻器
导电体
纳米技术
碳纤维
成核
光电子学
机制(生物学)
超级电容器
电极
计算机科学
电子工程
物理
化学
电容
人工神经网络
复合材料
工程类
复合数
机器学习
量子力学
有机化学
物理化学
作者
Tianqi Yu,Yong Fang,Xinyue Chen,Min Liu,Dong Wang,Songqin Liu,Wei Lei,Helong Jiang,Suhaidi Shafie,Mohd Nazim Mohtar,Likun Pan,Zhiwei Zhao
出处
期刊:Materials horizons
[Royal Society of Chemistry]
日期:2023-01-01
卷期号:10 (6): 2181-2190
被引量:18
摘要
As an emerging carbon-based material, carbon quantum dots (CQDs) have shown unstoppable prospects in the field of bionic electronics with their outstanding optoelectronic properties and unique biocompatible characteristics. In this study, a novel CQD-based memristor is proposed for neuromorphic computing. Unlike the models that rely on the formation and rupturing of conductive filaments, it is speculated that the resistance switching mechanism of CQD-based memristors is due to the conductive path caused by the hybridization state transition of the sp2 carbon domain and sp3 carbon domain induced by the reversible electric field. This avoids the drawback of uncontrollable nucleation sites leading to the random formation of conductive filaments in resistive switching. Importantly, it illustrates that the coefficient of variation (CV) of the threshold voltage can be as low as -1.551% and 0.083%, which confirms the remarkable uniform switching characteristics. Interestingly, the Pavlov's dog reflection as an important biological behavior can be demonstrated by the samples. Finally, the accuracy recognition rate of MNIST handwriting can reach up to 96.7%, which is very close to the ideal number (97.8%). A carbon-based memristor based on a new mechanism presented provides new possibilities for the improvement of brain-like computing.
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