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Ferroelectric tunnel junctions with 5 nm-thick HZO for tunable synaptic plasticity and neuromorphic computingopen access

Authors
Shin, JioSeo, EunchoYoun, ChaewonKim, Sungjun
Issue Date
Jul-2025
Publisher
Elsevier B.V.
Keywords
Neuromorphic computing; Ferroelectric; Synaptic plasticity; HZO; Memristor; Depolarization field
Citation
Journal of Alloys and Compounds, v.1036, pp 1 - 10
Pages
10
Indexed
SCIE
SCOPUS
Journal Title
Journal of Alloys and Compounds
Volume
1036
Start Page
1
End Page
10
URI
https://scholarworks.dongguk.edu/handle/sw.dongguk/58668
DOI
10.1016/j.jallcom.2025.181869
ISSN
0925-8388
1873-4669
Abstract
Hafnium oxide-based ferroelectric tunnel junctions (FTJs) have emerged as promising candidates for next-generation neuromorphic computing due to their ability to function as memristive devices. Their CMOS compatibility and low power consumption make them attractive for synaptic applications in artificial neural networks. The electrical properties of FTJs are significantly influenced by the thickness of the ferroelectric layer. In this study, we investigated the electrical characteristics, including remanent polarization (P-r) and tunneling electroresistance (TER) ratio, of FTJs with hafnium zirconium oxide (HZO) thicknesses of 5 nm, 7 nm, and 10 nm. Among these, the device with a 5 nm HZO layer exhibited the best performance, achieving a maximum 2 P-r of similar to 47.33 mu C/cm(2) and a maximum TER of similar to 2974.44 %. Furthermore, we explored the short-term memory characteristics and synaptic properties of this device, demonstrating its potential for neuromorphic computing applications. Our findings confirm the transition from short-term to long-term memory, mimicking human brain functionality under varying input pulse conditions. Finally, integrating this device as the reservoir layer in a reservoir computing system enabled high classification accuracies of 98.24 % on MNIST and 87.01 % on Fashion MNIST, highlighting its feasibility for neuromorphic systems.
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