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Highly-packed self-assembled graphene oxide film-integrated resistive random-access memory on a silicon substrate for neuromorphic application

Cited 1 time in Web of Science Cited 1 time in Scopus
Authors

Choi, Hyun-Seok; Lee, Jihye; Kim, Boram; Lee, Jaehong; Park, Byung-Gook; Kim, Yoon; Hong, Suck Won

Issue Date
2022-10
Publisher
Institute of Physics Publishing
Citation
Nanotechnology, Vol.33 No.43, p. ac805d
Abstract
© 2022 IOP Publishing Ltd.Resistive random-access memories (RRAMs) based on metal-oxide thin films have been studied extensively for application as synaptic devices in neuromorphic systems. The use of graphene oxide (GO) as a switching layer offers an exciting alternative to other materials such as metal-oxides. We present a newly developed RRAM device fabricated by implementing highly-packed GO layers on a highly doped Si wafer to yield a gradual modulation of the memory as a function of the number of input pulses. By using flow-enabled self-assembly, highly uniform GO thin films can be formed on flat Si wafers in a rapid and simple process. The switching mechanism was explored through proposed scenarios reconstructing the density change of the sp2 cluster in the GO layer, resulting in a gradual conductance modulation. We analyzed that the current in a low resistance state could flow by tunneling or hopping via clusters because the distance between the sp2 clusters in closely-packed GO layers is short. Finally, through a pattern-recognition simulation with a Modified National Institute of Standards and Technology database, the feasibility of using close-packed GO layers as synapse devices was successfully demonstrated.
ISSN
0957-4484
URI
https://hdl.handle.net/10371/186256
DOI
https://doi.org/10.1088/1361-6528/ac805d
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