Graphene oxide based synaptic memristor device for neuromorphic computing

Sahu, Dwipak Prasad and Jetty, Prabana and Jammalamadaka, Suryanarayana (2021) Graphene oxide based synaptic memristor device for neuromorphic computing. Nanotechnology, 32 (15). ISSN 0957-4484

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Abstract

Brain-inspired neuromorphic computing which consist neurons and synapses, with an ability to perform complex information processing has unfolded a new paradigm of computing to overcome the von Neumann bottleneck. Electronic synaptic memristor devices which can compete with the biological synapses are indeed significant for neuromorphic computing. In this work, we demonstrate our efforts to develop and realize the graphene oxide (GO) based memristor device as a synaptic device, which mimic as a biological synapse. Indeed, this device exhibits the essential synaptic learning behavior including analog memory characteristics, potentiation and depression. Furthermore, spike-timing-dependent-plasticity learning rule is mimicked by engineering the pre- A nd post-synaptic spikes. In addition, non-volatile properties such as endurance, retentivity, multilevel switching of the device are explored. These results suggest that Ag/GO/fluorine-doped tin oxide memristor device would indeed be a potential candidate for future neuromorphic computing applications. © 2021 IOP Publishing Ltd.

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IITH Creators:
IITH CreatorsORCiD
Jammalamadaka, Suryanarayanahttps://orcid.org/0000-0001-9235-7012
Item Type: Article
Additional Information: We would like to acknowledge Indian Institute of Technology, Hyderabad for providing financial support. Authors also thank DST - SERB (Grant No. CRG/2020/ 003497) for funding. The author Dwipak Prasad Sahu is thankful to the Department of Science and Technology, India (DST-INSPIRE) for the award of senior research fellowship (SRF).
Uncontrolled Keywords: Depression; Graphene oxide; Neuromorphic computing; Potentiation; RRAM; Synaptic device
Subjects: Physics
Divisions: Department of Physics
Depositing User: . LibTrainee 2021
Date Deposited: 24 Aug 2022 13:48
Last Modified: 24 Aug 2022 13:48
URI: http://raiith.iith.ac.in/id/eprint/10292
Publisher URL: http://doi.org/10.1088/1361-6528/abd978
OA policy: https://v2.sherpa.ac.uk/id/publication/11334
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