记忆电阻器
材料科学
铁电性
钙钛矿(结构)
光电子学
电气工程
电子工程
工程类
电介质
化学工程
作者
Dong-Ping Yang,Wen‐Min Zhong,Jun Li,Xin‐Gui Tang,Qijun Sun,Qiu‐Xiang Liu,Yanping Jiang
出处
期刊:Materials today electronics
[Elsevier BV]
日期:2024-12-12
卷期号:11: 100133-100133
被引量:2
标识
DOI:10.1016/j.mtelec.2024.100133
摘要
This study reports for the first time the application of double perovskite thin-film devices based on the Bi 2 FeCoO 6 (BFCO) compound in non-volatile ferroelectric memristors. By spin-coating BFCO onto an N-type silicon (N-Si) substrate, a P-N junction was formed, yielding a thin-film device with ferroelectric properties. The device demonstrated a maximum polarization value of 46.09 μC/cm² and a high switching ratio of 293, along with excellent long-term stability (over 7 days) and high repeatability (1000 cycles). Furthermore, we investigated the synaptic characteristics of the device, including short-term plasticity, paired-pulse facilitation, and long-term potentiation/inhibition behaviors. By designing a confusion matrix recognition scenario with a binary neural network, we validated the potential of double perovskite ferroelectric memristors in intelligent learning applications. Additionally, leveraging the synaptic plasticity of the device, we developed a modal storage memory and recognition system for human emotions. This work not only provides new insights into the development of high-performance double perovskite ferroelectric memristors but also lays the foundation for optimizing synaptic performance in intelligent learning applications.
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