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Cited 3 time in webofscience Cited 2 time in scopus
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Analog Synaptic Transistor with Al-Doped HfO2Ferroelectric Thin Film

Authors
Kim, DuhoJeon, Yu-RimKu, BoncheolChung, ChulwonKim, Tae HeunYang, SangheokWon, UiyeonJeong, TaehoChoi, Changhwan
Issue Date
10-Nov-2021
Publisher
AMER CHEMICAL SOC
Keywords
Al-doped HfO2; multilevel polarization; ferroelectric thin-film transistor; analog synaptic device; neuromorphic computing
Citation
ACS APPLIED MATERIALS & INTERFACES, v.13, no.44, pp.52743 - 52753
Indexed
SCIE
SCOPUS
Journal Title
ACS APPLIED MATERIALS & INTERFACES
Volume
13
Number
44
Start Page
52743
End Page
52753
URI
https://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/140321
DOI
10.1021/acsami.1c12735
ISSN
1944-8244
Abstract
Neuromorphic computing has garnered significant attention because it can overcome the limitations of the current von-Neumann computing system. Analog synaptic devices are essential for realizing hardware-based artificial neuromorphic devices; however, only a few systematic studies in terms of both synaptic materials and device structures have been conducted so far, and thus, further research is required in this direction. In this study, we demonstrate the synaptic characteristics of a ferroelectric material-based thin-film transistor (FeTFT) that uses partial switching of ferroelectric polarization to implement analog conductance modulation. For a ferroelectric material, an aluminum-doped hafnium oxide (Al-doped HfO2) thin film was prepared by atomic layer deposition. As an analog synaptic device, our FeTFT successfully emulated short-term plasticity and long-term plasticity characteristics, such as paired-pulse facilitation and spike timing-dependent plasticity. In addition, we obtained potentiation/depression weight updates with high linearity, an on/off ratio, and low cycle-to-cycle variation by adjusting the amplitude and number of input pulses. In the simulation trained with optimized potentiation/depression conditions, we achieved a pattern recognition accuracy of approximately 90% for the Modified National Institute of Standard and Technology (MNIST) handwritten data set. Our results indicated that ferroelectric transistors can be used as an alternative artificial synapse.
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