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Multilevel switching characteristics of Si3N4-based nano-wedge resistive switching memory and array simulation for in-memory computing application

Authors
Lee, D.K.Kim, M.-H.Bang, S.Kim, T.-H.Kim, S.Cho, S.Park, B.-G.
Issue Date
Aug-2020
Publisher
MDPI AG
Keywords
Array; Nano-wedge; Neural network; Resistive switching random-access memory; Switching layer; Switching process; TMAH
Citation
Electronics (Switzerland), v.9, no.8, pp.1 - 8
Journal Title
Electronics (Switzerland)
Volume
9
Number
8
Start Page
1
End Page
8
URI
https://scholarworks.bwise.kr/gachon/handle/2020.sw.gachon/78268
DOI
10.3390/electronics9081228
ISSN
2079-9292
Abstract
In this research, nano-wedge resistive switching random-access memory (ReRAM) based on a Si3N4 switching layer and silicon bottom electrode was fabricated, and its multilevel switching characteristics were investigated. The wedge bottom electrode was formed by a tetramethyl ammonium hydroxide (TMAH) wet-etching process. The nano-wedge ReRAM was demonstrated to have different reset current levels by varying the compliance currents. To explain the effect of modulating the compliance currents, the switching characteristics of both the SET and RESET behaviors were shown. After measuring the device under four different compliance currents, it was proved to have different current levels due to an inhibited resistive state after a SET switching process. Furthermore, SPICE circuit simulation was carried out to show the effect of line resistance on current summation for the array sizes of 8 × 8 and 16 × 16. These results indicate the importance of minimizing the line resistance for successful implementation as a hardware-based neural network. © 2020 by the authors. Licensee MDPI, Basel, Switzerland.
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