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Gao P, Duan M, Yang G, Zhang W, Jia C. Ultralow Energy Consumption and Fast Neuromorphic Computing Based on La 0.1Bi 0.9FeO 3 Ferroelectric Tunnel Junctions. NANO LETTERS 2024. [PMID: 39172999 DOI: 10.1021/acs.nanolett.4c01924] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 08/24/2024]
Abstract
Low-power and fast artificial neural network devices represent the direction in developing analogue neural networks. Here, an ultralow power consumption (0.8 fJ) and rapid (100 ns) La0.1Bi0.9FeO3/La0.7Sr0.3MnO3 ferroelectric tunnel junction artificial synapse has been developed to emulate the biological neural networks. The visual memory and forgetting functionalities have been emulated based on long-term potentiation and depression with good linearity. Moreover, with a single device, logical operations of "AND" and "OR" are implemented, and an artificial neural network was constructed with a recognition accuracy of 96%. Especially for noisy data sets, the recognition speed is faster after preprocessing by the device in the present work. This sets the stage for highly reliable and repeatable unsupervised learning.
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Affiliation(s)
- Pan Gao
- Henan Key Laboratory of Quantum Materials and Quantum Energy, School of Quantum Information Future Technology, Henan University, Kaifeng 475004, China
| | - Mengyuan Duan
- Henan Key Laboratory of Quantum Materials and Quantum Energy, School of Quantum Information Future Technology, Henan University, Kaifeng 475004, China
| | - Guanghong Yang
- Key Lab for Special Functional Materials of Ministry of Education, School of Materials, Henan University, Kaifeng 475004, P. R. China
| | - Weifeng Zhang
- Henan Key Laboratory of Quantum Materials and Quantum Energy, School of Quantum Information Future Technology, Henan University, Kaifeng 475004, China
- Institute of Quantum Materials and Physics, Henan Academy of Sciences, Zhengzhou 450046, China
| | - Caihong Jia
- Henan Key Laboratory of Quantum Materials and Quantum Energy, School of Quantum Information Future Technology, Henan University, Kaifeng 475004, China
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Zhang X, Wei H, Wu Y, Yang T, Cao B. Giant tunnel resistance effect in (SrTiO 3) 2/(BaTiO 3) 4/(CaTiO 3) 2 asymmetric superlattice with enhanced polarization. Phys Chem Chem Phys 2024; 26:2168-2174. [PMID: 38132888 DOI: 10.1039/d3cp04608g] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/23/2023]
Abstract
In this work, we report the effectively enhanced tunneling electroresistance effect in Au/(SrTiO3)2/(BaTiO3)4/(CaTiO3)2/Nb:SrTiO3 superlattice ferroelectric tunnel junction (FTJ). The stable polarization switching and enhanced ferroelectricity were achieved in the nanoscale thickness high-quality epitaxial superlattice. A high ON/OFF current ratio of more than 105 was obtained at room temperature, which is an order of magnitude larger than the BaTiO3 FTJ with the same structure. Nonvolatile resistance switching controlled by nonvolatile polarization switching was observed in the superlattice FTJ. Driven by increased polarization and intrinsic asymmetric ferroelectricity, a highly asymmetric depolarization field is generated compared with the Au/BaTiO3/Nb:SrTiO3 FTJ, resulting in an enhanced tunneling electroresistance effect. These results provide a potential way to construct FTJ memory devices by constructing asymmetric three-component ferroelectric superlattices.
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Affiliation(s)
- Xiubing Zhang
- School of Physics and Physical Engineering, Qufu Normal University, Qufu 273165, China.
| | - Haoming Wei
- School of Physics and Physical Engineering, Qufu Normal University, Qufu 273165, China.
| | - Yangqing Wu
- School of Physics and Physical Engineering, Qufu Normal University, Qufu 273165, China.
| | - Tengzhou Yang
- School of Physics and Physical Engineering, Qufu Normal University, Qufu 273165, China.
| | - Bingqiang Cao
- School of Material Science and Engineering, University of Jinan, Jinan 250022, Shandong, China.
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Song Y, Wu Q, Jia C, Gao Z, Zhang W. High-performance ferroelectric nonvolatile memory based on Gd-and Ni-codoped BiFeO 3 films. RSC Adv 2022; 12:15814-15821. [PMID: 35685697 PMCID: PMC9131732 DOI: 10.1039/d2ra01156e] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/21/2022] [Accepted: 05/03/2022] [Indexed: 11/21/2022] Open
Abstract
BiFeO3 (BFO), Bi0.92Gd0.08FeO3 (BGFO) and Bi0.92Gd0.08Fe0.95Ni0.05O3 (BGFNO) films are epitaxially grown on 0.7 wt% Nb-SrTiO3 (NSTO) substrates. The strong ferroelectric property in BGFNO film is confirmed by piezoresponse force microscopy (PFM) and polarization versus voltage (P-V) measurement. It is also found that the Au/BGFNO/NSTO devices possess a ferroelectric resistance switching (RS) effect. Gd- and Ni-codoped BiFeO3 is found to strongly enhance the resistance on/off ratio. A resistance on/off ratio as large as 3 × 106 is achieved with an applied pulse voltage of -8 V and +4 V. In addition, the devices exhibit excellent retention and anti-fatigue characteristics. The memristor behavior of Au/BGFNO/NSTO is attributed to the switching of polarization states, which modulate the width and height of the barrier at the BGFNO/NSTO interface. The excellent resistive switching properties in Au/BGFNO/NSTO devices indicate the promising application in nonvolatile memory.
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Affiliation(s)
- Yanling Song
- Henan Key Laboratory of Photovoltaic Materials, Center for Topological Functional Materials, Henan University Kaifeng 475004 People's Republic of China
| | - Qiyuan Wu
- Henan Key Laboratory of Photovoltaic Materials, Center for Topological Functional Materials, Henan University Kaifeng 475004 People's Republic of China
| | - Caihong Jia
- Henan Key Laboratory of Photovoltaic Materials, Center for Topological Functional Materials, Henan University Kaifeng 475004 People's Republic of China
| | - Zhaomeng Gao
- Key Laboratory of Microelectronics Devices & Integrated Technology, Institute of Microelectronics of Chinese Academy of Sciences Beijing 100029 China
| | - Weifeng Zhang
- Henan Key Laboratory of Photovoltaic Materials, Center for Topological Functional Materials, Henan University Kaifeng 475004 People's Republic of China
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Sun B, Zhou G, Sun L, Zhao H, Chen Y, Yang F, Zhao Y, Song Q. ABO 3 multiferroic perovskite materials for memristive memory and neuromorphic computing. NANOSCALE HORIZONS 2021; 6:939-970. [PMID: 34652346 DOI: 10.1039/d1nh00292a] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/13/2023]
Abstract
The unique electron spin, transfer, polarization and magnetoelectric coupling characteristics of ABO3 multiferroic perovskite materials make them promising candidates for application in multifunctional nanoelectronic devices. Reversible ferroelectric polarization, controllable defect concentration and domain wall movement originated from the ABO3 multiferroic perovskite materials promotes its memristive effect, which further highlights data storage, information processing and neuromorphic computing in diverse artificial intelligence applications. In particular, ion doping, electrode selection, and interface modulation have been demonstrated in ABO3-based memristive devices for ultrahigh data storage, ultrafast information processing, and efficient neuromorphic computing. These approaches presented today including controlling the dopant in the active layer, altering the oxygen vacancy distribution, modulating the diffusion depth of ions, and constructing the interface-dependent band structure were believed to be efficient methods for obtaining unique resistive switching (RS) behavior for various applications. In this review, internal physical dynamics, preparation technologies, and modulation methods are systemically examined as well as the progress, challenges, and possible solutions are proposed for next generation emerging ABO3-based memristive application in artificial intelligence.
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Affiliation(s)
- Bai Sun
- School of Physical Science and Technology, Key Laboratory of Advanced Technology of Materials (Ministry of Education of China), Southwest Jiaotong University, Chengdu, Sichuan 610031, China.
- Superconductivity and New Energy R&D Center, Southwest Jiaotong University, Chengdu, Sichuan 610031, China
| | - Guangdong Zhou
- School of Artificial Intelligence and School of Materials and Energy, Southwest University, Chongqing 400715, China.
| | - Linfeng Sun
- Centre for Quantum Physics, Key Laboratory of Advanced Optoelectronic Quantum Architecture and Measurement (MOE), School of Physics, Beijing Institute of Technology, Beijing 100081, China
| | - Hongbin Zhao
- State Key Laboratory of Advanced Materials for Smart Sensing, General Research Institute for Nonferrous Metals, Beijing, 100088, China
| | - Yuanzheng Chen
- School of Physical Science and Technology, Key Laboratory of Advanced Technology of Materials (Ministry of Education of China), Southwest Jiaotong University, Chengdu, Sichuan 610031, China.
| | - Feng Yang
- Superconductivity and New Energy R&D Center, Southwest Jiaotong University, Chengdu, Sichuan 610031, China
| | - Yong Zhao
- School of Physical Science and Technology, Key Laboratory of Advanced Technology of Materials (Ministry of Education of China), Southwest Jiaotong University, Chengdu, Sichuan 610031, China.
- Superconductivity and New Energy R&D Center, Southwest Jiaotong University, Chengdu, Sichuan 610031, China
| | - Qunliang Song
- School of Artificial Intelligence and School of Materials and Energy, Southwest University, Chongqing 400715, China.
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Kumari A, Kumari K, Aljawfi RN, Alvi PA, Dalela S, Ahmad MM, Chawla AK, Kumar R, Vij A, Kumar S. Role of La substitution on structural, optical, and multiferroic properties of BiFeO3 nanoparticles. APPLIED NANOSCIENCE 2021. [DOI: 10.1007/s13204-021-01844-1] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/24/2022]
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