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Ferroelectric memristors optimized in thickness for short-term memory-driven reservoir computingopen access

Authors
Park, JunhyeokKim, Sungjun
Issue Date
Jan-2026
Publisher
Royal Society of Chemistry
Citation
Journal of Materials Chemistry C
Indexed
SCIE
SCOPUS
Journal Title
Journal of Materials Chemistry C
URI
https://scholarworks.dongguk.edu/handle/sw.dongguk/63727
DOI
10.1039/d5tc03983e
ISSN
2050-7526
2050-7534
Abstract
In this work, Mo/Hf0.5Zr0.5O2 (HZO)/n+ Si ferroelectric memristors were fabricated, and their thickness-dependent properties were systematically analyzed. The optimized 5 nm HZO device exhibited stabilized orthorhombic phase formation, yielding the highest remanent polarization (2Pr = 24.96 mu C cm-2), a tunneling electro-resistance (TER) ratio of 2474.05%, and a rectifying ratio of 4530.78. These superior properties enabled reliable multilevel cell (MLC) operation, suppressed leakage currents, and minimized sneak paths in crossbar arrays. Short-term memory (STM) characteristics were experimentally confirmed through paired-pulse facilitation (PPF) and retention measurements, validating the device's ability to emulate synaptic dynamics. Furthermore, synaptic plasticity was successfully reproduced under spike-amplitude dependent plasticity (SADP), spike-duration dependent plasticity (SDDP), spike-rate dependent plasticity (SRDP), and spike-number dependent plasticity (SNDP) conditions. Leveraging these STM features, reservoir computing (RC) simulations achieved high recognition accuracy for both MNIST and Hand MNIST datasets, with the latter reaching 98.71%, thereby demonstrating efficient processing of complex gesture data. These findings highlight the potential of the 5 nm HZO ferroelectric memristor as an optimized device for short-term memory based RC systems, offering strong potential for neuromorphic computing and next-generation memory technologies and computing.
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