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Spike-time dependent plasticity of tailored ZnO nanorod-based resistive memory for synaptic learning

Authors :
Shubham V. Patil
Navaj B. Mullani
Kiran Nirmal
Gihwan Hyun
Batyrbek Alimkhanuly
Rajanish K. Kamat
Jun Hong Park
Sanghoek Kim
Tukaram D. Dongale
Seunghyun Lee
Source :
Journal of Science: Advanced Materials and Devices, Vol 8, Iss 4, Pp 100617- (2023)
Publication Year :
2023
Publisher :
Elsevier, 2023.

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.

Details

Language :
English
ISSN :
24682179
Volume :
8
Issue :
4
Database :
Directory of Open Access Journals
Journal :
Journal of Science: Advanced Materials and Devices
Publication Type :
Academic Journal
Accession number :
edsdoj.4976efd68f6d409185964cf172de760e
Document Type :
article
Full Text :
https://doi.org/10.1016/j.jsamd.2023.100617