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Volume 9
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10.3390/electronics9081228
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Article

Multilevel Switching Characteristics of Si3N4-Based Nano-Wedge Resistive Switching Memory and Array Simulation for In-Memory Computing Application

by
Dong Keun Lee
1,2,
Min-Hwi Kim
1,2,
Suhyun Bang
1,2,
Tae-Hyeon Kim
1,2,
Sungjun Kim
3,
Seongjae Cho
4 and
Byung-Gook Park
1,2,*
1
Department of Electrical and Computer Engineering, Seoul National University, Seoul 08826, Korea
2
Inter-University Semiconductor Research Center, Seoul National University, Seoul 08826, Korea
3
Division of Electronics and Electrical Engineering, Dongguk University, Seoul 04620, Korea
4
Department of IT Convergence Engineering, Gachon University, Gyeonggi-do 13120, Korea
*
Author to whom correspondence should be addressed.
Electronics 2020, 9(8), 1228; https://doi.org/10.3390/electronics9081228
Submission received: 6 July 2020 / Revised: 20 July 2020 / Accepted: 28 July 2020 / Published: 30 July 2020
(This article belongs to the Section Semiconductor Devices)
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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.
Keywords: nano-wedge; resistive switching random-access memory; switching layer; TMAH; switching process; array; neural network nano-wedge; resistive switching random-access memory; switching layer; TMAH; switching process; array; neural network

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MDPI and ACS Style

Lee, D.K.; Kim, M.-H.; Bang, S.; Kim, T.-H.; Kim, S.; Cho, S.; Park, B.-G. Multilevel Switching Characteristics of Si3N4-Based Nano-Wedge Resistive Switching Memory and Array Simulation for In-Memory Computing Application. Electronics 2020, 9, 1228. https://doi.org/10.3390/electronics9081228

AMA Style

Lee DK, Kim M-H, Bang S, Kim T-H, Kim S, Cho S, Park B-G. Multilevel Switching Characteristics of Si3N4-Based Nano-Wedge Resistive Switching Memory and Array Simulation for In-Memory Computing Application. Electronics. 2020; 9(8):1228. https://doi.org/10.3390/electronics9081228

Chicago/Turabian Style

Lee, Dong Keun, Min-Hwi Kim, Suhyun Bang, Tae-Hyeon Kim, Sungjun Kim, Seongjae Cho, and Byung-Gook Park. 2020. "Multilevel Switching Characteristics of Si3N4-Based Nano-Wedge Resistive Switching Memory and Array Simulation for In-Memory Computing Application" Electronics 9, no. 8: 1228. https://doi.org/10.3390/electronics9081228

APA Style

Lee, D. K., Kim, M.-H., Bang, S., Kim, T.-H., Kim, S., Cho, S., & Park, B.-G. (2020). Multilevel Switching Characteristics of Si3N4-Based Nano-Wedge Resistive Switching Memory and Array Simulation for In-Memory Computing Application. Electronics, 9(8), 1228. https://doi.org/10.3390/electronics9081228

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