Ferroelectric memristors based on double perovskite Bi2FeCoO6 for synaptic performance and human expression recognition storage

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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Publication Details

Journal
Materials Today Electronics
Published
2024-12-12
DOI
https://doi.org/10.1016/j.mtelec.2024.100133
Citations
2
Primary Topic
Advanced Memory and Neural Computing
Type
article
Field-Weighted Citation Impact
0.42
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article

Ferroelectric memristors based on double perovskite Bi2FeCoO6 for synaptic performance and human expression recognition storage

Qijun Sun, Qiu‐Xiang Liu, Wen‐Min Zhong, Xin‐Gui Tang et al.
2 citations
Materials Today Electronics
Advanced Memory and Neural Computing
0.42
article

Ferroelectric memristors based on double perovskite Bi2FeCoO6 for synaptic performance and human expression recognition storage

Qijun Sun, Qiu‐Xiang Liu, Wen‐Min Zhong, Xin‐Gui Tang, Yanping Jiang, Dong-Ping Yang, Jun Li
article en
2 citations

Abstract

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.

Materials Today ElectronicsVol. 11
Guangdong University of Technology (CN), Key Laboratory of Guangdong Province (CN), Guangzhou Panyu Polytechnic (CN)
Openalex Percentile: Top 36%
Advanced Memory and Neural Computing
0.42
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Ferroelectric memristors based on double perovskite Bi2FeCoO6 for synaptic performance and human expression recognition storage — Qijun Sun, Qiu‐Xiang Liu, et al. · Materials Today Electronics (2024) | TGRS Research Map | TGRS