Ferroelectric synaptic devices based on CMOS-compatible HfAlOx for neuromorphic and reservoir computing applicationsopen access
- Authors
- Kim, Dahye; Kim, Jihyung; Yun, Seokyeon; Lee, Jungwoo; Seo, Euncho; Kim, Sungjun
- Issue Date
- May-2023
- Publisher
- Royal Society of Chemistry
- Keywords
- Aluminum Compounds; Cmos Integrated Circuits; Ferroelectricity; Tunnel Junctions; Atomic Radius; Cmos Compatibility; Cmos Compatible; Computing Applications; Condition; Ferroelectric Tunnel Junctions; Low Power; Memristor; Neuromorphic Computing; Reservoir Computing; Hafnium Oxides; Article; Facilitation; Feasibility Study; Polarization; Spike; Synapse; Thickness
- Citation
- Nanoscale, v.15, no.18, pp 8366 - 8376
- Pages
- 11
- Indexed
- SCIE
SCOPUS
- Journal Title
- Nanoscale
- Volume
- 15
- Number
- 18
- Start Page
- 8366
- End Page
- 8376
- URI
- https://scholarworks.dongguk.edu/handle/sw.dongguk/21217
- DOI
- 10.1039/d3nr01294h
- ISSN
- 2040-3364
2040-3372
- Abstract
- The hafnium oxide-based ferroelectric tunnel junction (FTJ) has been actively researched because of desirable advantages such as low power and CMOS compatibility to operate as a memristor. In the case of HfAlOx (HAO), the remanent polarization (P-r) value is high and the atomic radius of Al is smaller than that of Hf; therefore, ferroelectricity can be better induced without mechanical force. In this paper, we propose an FTJ using HAO as a ferroelectric layer through electrical analysis and experiments; further, we experimentally demonstrate its capability as a synaptic device. Moreover, we evaluate the maximum 2P(r) and TER value of the device according to the difference in conditions of thickness and cell area. The optimized device conditions are analyzed, and a large value of 2P(r) (>similar to 43 mu C cm(-2)) is obtained. Furthermore, we show that paired-pulse facilitation, paired-pulse depression, and spike-timing-dependent plasticity can be utilized in HAO-based FTJs. In addition, this study demonstrates the use of an FTJ device as a physical reservoir to implement reservoir computing. Through a series of processes, the synaptic properties of FTJs are verified for the feasibility of their implementation as an artificial synaptic device.
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Collections - College of Engineering > Department of Electronics and Electrical Engineering > 1. Journal Articles

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