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Cinar I. Improving structural and magnetic properties of zinc stannate thin films through nickel doping via sol-gel method. Sci Rep 2024; 14:14808. [PMID: 38926404 PMCID: PMC11208567 DOI: 10.1038/s41598-024-63209-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/28/2024] [Accepted: 05/27/2024] [Indexed: 06/28/2024] Open
Abstract
Ternary oxides are currently emerging as promising materials for optoelectronic devices and spintronics, surpassing binary oxides in terms of their superior properties. Among these, zinc stannate (Zn2SnO4) stands out due to its stability and attractive physical characteristics. However, despite its outstanding attributes, there is a need to further develop its magnetic properties for spintronic applications. In this study, Ni-doped Zn2SnO4 thin films were synthesized using the sol-gel method, and their magnetic characteristics were investigated for the first time. X-ray diffraction analysis confirmed the high crystallinity of the synthesized samples, even after the incorporation of Ni dopants, without any secondary phases. SEM imaging revealed the cubic structure morphology of the thin films. An increase in the bandgap, dependent on the Ni dopant concentration, was observed for doped zinc stannate, suggesting potential for tailored electronic properties. FTIR spectroscopy confirmed the presence of functional groups within the material. Notably, the magnetic properties of the thin films were analyzed using a vibrating sample magnetometer (VSM), revealing diamagnetic behavior for pure zinc stannate and ferromagnetic properties for Ni-doped Zn2SnO4, which increased with dopant concentration. Overall, the results highlight the excellent structural, optical, and ferromagnetic properties of Ni-doped Zn2SnO4 thin films, positioning them for diverse applications, particularly in optoelectronic and spintronic technology.
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Affiliation(s)
- Ibrahim Cinar
- Department of Medical Services and Techniques, Karamanoglu Mehmetbey University, 70100, Karaman, Turkey.
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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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