Enhanced Giant Ferroelectric Tunneling Electroresistance in 2D Ruddlesden–Popper Oxides

Ferroelectric tunnel junctions (FTJs) based on ferroelectric switching and quantum tunneling effects with thickness down to a few unit cells have been explored for applications of two-dimensional (2D) electronic devices in data storage and neural networks. As a key performance indicator, the enhanced tunneling electrosistance (TER) ratio provides a broader dynamic range for precise modulation of synaptic weights, improving the stability and accuracy of neural networks. Herein, we report an observation of pronounced enhancement in the TER ratio by over 4 orders of magnitude through the fabrication of large-scale heterostructures combining bismuth ferrite with two-dimensional Ruddlesden-Popper oxide Bi<sub>2</sub>FeO<sub>4</sub>. The significant difference in Schottky barrier height between Bi<sub>2</sub>FeO<sub>4</sub> and electrodes leads to a remarkable TER value of 7.8 × 10<sup>6</sup>. Moreover, benefiting from the enhanced conductance contrast between the high resistance state (HRS) and low resistance state (LRS), we demonstrate image recognition and dehaze processing using artificial neural synapses based on these FTJs. These results indicate that giant barrier height modulation can be realized through 2D Ruddlesden-Popper oxides, providing a facile technique for high-density in-memory computing applications.

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Publication Details

Journal
ACS Nano
Published
2025-09-08
DOI
https://doi.org/10.1021/acsnano.5c08125
Citations
2
Primary Topic
Advanced Memory and Neural Computing
Type
article
Field-Weighted Citation Impact
1.46
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article

Enhanced Giant Ferroelectric Tunneling Electroresistance in 2D Ruddlesden–Popper Oxides

Hui Zeng, Chao Jiang, Ruiqing Cheng, Ziren Xiong et al.
2 citations
ACS Nano
Advanced Memory and Neural Computing
1.46
article

Enhanced Giant Ferroelectric Tunneling Electroresistance in 2D Ruddlesden–Popper Oxides

Hui Zeng, Chao Jiang, Ruiqing Cheng, Ziren Xiong, Lei Yin, Hao Wang, Hao Zhu, Jun He, Yao Wen, Xiaolin Zhang, Jiaqing Qi, Yangyuan Tu
article en
2 citations

Abstract

Ferroelectric tunnel junctions (FTJs) based on ferroelectric switching and quantum tunneling effects with thickness down to a few unit cells have been explored for applications of two-dimensional (2D) electronic devices in data storage and neural networks. As a key performance indicator, the enhanced tunneling electrosistance (TER) ratio provides a broader dynamic range for precise modulation of synaptic weights, improving the stability and accuracy of neural networks. Herein, we report an observation of pronounced enhancement in the TER ratio by over 4 orders of magnitude through the fabrication of large-scale heterostructures combining bismuth ferrite with two-dimensional Ruddlesden-Popper oxide Bi<sub>2</sub>FeO<sub>4</sub>. The significant difference in Schottky barrier height between Bi<sub>2</sub>FeO<sub>4</sub> and electrodes leads to a remarkable TER value of 7.8 × 10<sup>6</sup>. Moreover, benefiting from the enhanced conductance contrast between the high resistance state (HRS) and low resistance state (LRS), we demonstrate image recognition and dehaze processing using artificial neural synapses based on these FTJs. These results indicate that giant barrier height modulation can be realized through 2D Ruddlesden-Popper oxides, providing a facile technique for high-density in-memory computing applications.

ACS NanoVol. 19(37)
Ministry of Education of the People's Republic of China (CN), Nankai University (CN), Wuhan University (CN), University of Chinese Academy of Sciences (CN), Henan Normal University (CN), Wuhan Institute of Technology (CN)
Openalex Percentile: Top 15%
Advanced Memory and Neural Computing
1.46
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