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Ferroelectric memristors optimized in thickness for short-term memory-driven reservoir computing
| DC Field | Value | Language |
|---|---|---|
| dc.contributor.author | Park, Junhyeok | - |
| dc.contributor.author | Kim, Sungjun | - |
| dc.date.accessioned | 2026-02-19T06:00:15Z | - |
| dc.date.available | 2026-02-19T06:00:15Z | - |
| dc.date.issued | 2026-01 | - |
| dc.identifier.issn | 2050-7526 | - |
| dc.identifier.issn | 2050-7534 | - |
| dc.identifier.uri | https://scholarworks.dongguk.edu/handle/sw.dongguk/63727 | - |
| dc.description.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. | - |
| dc.language | 영어 | - |
| dc.language.iso | ENG | - |
| dc.publisher | Royal Society of Chemistry | - |
| dc.title | Ferroelectric memristors optimized in thickness for short-term memory-driven reservoir computing | - |
| dc.type | Article | - |
| dc.publisher.location | 영국 | - |
| dc.identifier.doi | 10.1039/d5tc03983e | - |
| dc.identifier.scopusid | 2-s2.0-105030532666 | - |
| dc.identifier.wosid | 001681432200001 | - |
| dc.identifier.bibliographicCitation | Journal of Materials Chemistry C | - |
| dc.citation.title | Journal of Materials Chemistry C | - |
| dc.type.docType | Article; Early Access | - |
| dc.description.isOpenAccess | Y | - |
| dc.description.journalRegisteredClass | scie | - |
| dc.description.journalRegisteredClass | scopus | - |
| dc.relation.journalResearchArea | Materials Science | - |
| dc.relation.journalResearchArea | Physics | - |
| dc.relation.journalWebOfScienceCategory | Materials Science, Multidisciplinary | - |
| dc.relation.journalWebOfScienceCategory | Physics, Applied | - |
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