| 1. |
- Devi, Chandni, et al.
(författare)
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High sodium ionic conductivity in PEO/PVP solid polymer electrolytes with InAs nanowire fillers
- 2021
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Ingår i: Scientific Reports. - London : Nature Publishing Group. - 2045-2322. ; 11:1
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Tidskriftsartikel (refereegranskat)abstract
- Solid-state sodium ion batteries are frequently referred to as the most promising technology for next-generation energy storage applications. However, developing a suitable solid electrolyte with high ionic conductivity, excellent electrolyte–electrode interfaces, and a wide electrochemical stability window, remains a major challenge. Although solid-polymer electrolytes have attracted great interest due to their low cost, low density and very good processability, they generally have significantly lower ionic conductivity and poor mechanical strength. Here, we report on the development of a low-cost composite solid polymer electrolyte comprised of poly(ethylene oxide), poly(vinylpyrrolidone) and sodium hexafluorophosphate, mixed with indium arsenide nanowires. We show that the addition of 1.0% by weight of indium arsenide nanowires increases the sodium ion conductivity in the polymer to 1.50 × 10−4 Scm−1 at 40 °C. In order to explain this remarkable characteristic, we propose a new transport model in which sodium ions hop between close-spaced defect sites present on the surface of the nanowires, forming an effective complex conductive percolation network. Our work represents a significant advance in the development of novel solid polymer electrolytes with embedded engineered ultrafast 1D percolation networks for near-future generations of low-cost, high-performance batteries with excellent energy storage capabilities. © 2021, The Author(s).
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| 2. |
- Kumari, Renu, et al.
(författare)
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Artificial synaptic characteristics of PVA:ZnO nanocomposite memristive devices
- 2023
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Ingår i: APL Materials. - Melville : American Institute of Physics (AIP). - 2166-532X. ; 11:10
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Tidskriftsartikel (refereegranskat)abstract
- Computational efficiency is significantly enhanced using artificial neural network-based computing. A two-terminal memristive device is a powerful electronic device that can mimic the behavior of a biological synapse in addition to storing information and performing logic operations. This work focuses on the fabrication of a memristive device that utilizes a resistive switching layer composed of polyvinyl alcohol infused with ZnO nanoparticles. By incorporating ZnO nanoparticles into the polymer film, the fabricated memristive devices exhibit functionalities that closely resemble those of biological synapses, including short-term and long-term plasticity, paired-pulse facilitation, and spike time-dependent plasticity. These findings establish the ZnO nanoparticle-polymer nanocomposite as a highly promising material for future neuromorphic systems. © 2023 Author(s).
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