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Cited 9 time in webofscience Cited 11 time in scopus
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Spike-time dependent plasticity of tailored ZnO nanorod-based resistive memory for synaptic learningopen access

Authors
Patil, Shubham V.Mullani, Navaj B.Nirmal, KiranHyun, GihwanAlimkhanuly, BatyrbekKamat, Rajanish K.Park, Jun HongKim, SanghoekDongale, Tukaram D.Lee, Seunghyun
Issue Date
Dec-2023
Publisher
Elsevier B.V.
Keywords
Analog memristor; Nanochannel switching; Neuromorphic electron devices; Spike-time dependent plasticity
Citation
Journal of Science: Advanced Materials and Devices, v.8, no.4
Indexed
SCIE
SCOPUS
Journal Title
Journal of Science: Advanced Materials and Devices
Volume
8
Number
4
URI
https://scholarworks.gnu.ac.kr/handle/sw.gnu/67626
DOI
10.1016/j.jsamd.2023.100617
ISSN
2468-2284
2468-2179
Abstract
Metal oxide resistive memory is a potential device that can substantially influence the current roadmap for nonvolatile memory and neuromorphic computing. However, common amorphous oxide-based resistive random-access memory suffers from high forming voltages that complicate circuit design and abrupt SET behavior incompatible with analog weight updates. To overcome such limitations, wurtzite ZnO nanorods were synthesized on a fluorine-doped tin oxide (FTO) substrate and a bipolar resistive memory with the Ag/w-ZnO/FTO stacking sequence was fabricated. The hexagonal NR morphology of w-ZnO with controlled vertical growth and nanochannel formation between the NRs were produced by in situ crystalline growth. This morphology enabled a forming-free switching and an analog switching effect that emulated neuromorphic functionalities such as potentiation–depression and complex spike-time dependent plasticity-based Hebbian learning rules. Importantly, the device exhibited nonabrupt switching behavior suitable for analog weight updates in neuromorphic computing in contrast to conventional resistive memory. © 2023 Vietnam National University, Hanoi
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대학원 (나노신소재융합공학과)
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