Enhancing Energy Efficiency: Statistical Analysis of RRAM Operations using ZnO-based Approach

Usman Isyaku Bature; Illani Mohd Nawi; Mohd Haris Md Khir; Saeed S. Ba Hashwan; Furqan Zahoor; Mohammad Obaidur Rahman

doi:10.1109/SENNANO57767.2023.10352520

Enhancing Energy Efficiency: Statistical Analysis of RRAM Operations using ZnO-based Approach

Usman Isyaku Bature
, Illani Mohd Nawi
, Mohd Haris Md Khir
, Saeed S. Ba Hashwan
, Furqan Zahoor
, Mohammad Obaidur Rahman

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

RRAM has garnered significant attention from various perspectives; however, certain barriers hinder its widespread adoption. These challenges revolve around reliability and power operation, making their resolution crucial. This work highlights the effects of operating at high voltages (>10V), which also affect other memory technologies, including Flash memory. The study introduces an insightful approach involving voltage flow analysis coupled with exploring the fundamental thermal energy flow in ZnO-based RRAM stacks operating within 1.2V. The model adopts a two-dimensional arrangement in COMSOL Multiphysics and further employs MATLAB (LiveLinkTM). The research delves into the dynamic resistance switching process, elucidating the role of joule heating effects, field-driven ion transport, and the temperature influence when the operating voltage exceeds 1.2V, as depicted in various plots. This investigation advances our comprehension of the complex dynamics involved in RRAM operation and demonstrates methods to enhance device performance, improve reliability, and ensure long-term functionality in practical applications.

Original language	English
Title of host publication	2023 IEEE International Conference on Sensors and Nanotechnology, SENNANO 2023
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	150-153
Number of pages	4
ISBN (Electronic)	9798350333312
DOIs	https://doi.org/10.1109/SENNANO57767.2023.10352520
State	Published - 2023
Externally published	Yes
Event	2023 IEEE International Conference on Sensors and Nanotechnology, SENNANO 2023 - Putrajaya, Malaysia Duration: 26 Sep 2023 → 27 Sep 2023

Publication series

Name	2023 IEEE International Conference on Sensors and Nanotechnology, SENNANO 2023

Conference

Conference	2023 IEEE International Conference on Sensors and Nanotechnology, SENNANO 2023
Country/Territory	Malaysia
City	Putrajaya
Period	26/09/23 → 27/09/23

Bibliographical note

Publisher Copyright:
© 2023 IEEE.

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 7 Affordable and Clean Energy

Keywords

Energy efficiency
RRAM operations
Simulation
ZnO-based RRAM

ASJC Scopus subject areas

Electrical and Electronic Engineering
Materials Science (miscellaneous)
Electronic, Optical and Magnetic Materials
Polymers and Plastics
Instrumentation

Access to Document

10.1109/SENNANO57767.2023.10352520

Cite this

Bature, U. I., Mohd Nawi, I., Md Khir, M. H., Ba Hashwan, S. S., Zahoor, F., & Rahman, M. O. (2023). Enhancing Energy Efficiency: Statistical Analysis of RRAM Operations using ZnO-based Approach. In 2023 IEEE International Conference on Sensors and Nanotechnology, SENNANO 2023 (pp. 150-153). (2023 IEEE International Conference on Sensors and Nanotechnology, SENNANO 2023). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/SENNANO57767.2023.10352520

Bature, Usman Isyaku ; Mohd Nawi, Illani ; Md Khir, Mohd Haris et al. / Enhancing Energy Efficiency : Statistical Analysis of RRAM Operations using ZnO-based Approach. 2023 IEEE International Conference on Sensors and Nanotechnology, SENNANO 2023. Institute of Electrical and Electronics Engineers Inc., 2023. pp. 150-153 (2023 IEEE International Conference on Sensors and Nanotechnology, SENNANO 2023).

@inproceedings{f2a54941946740dfbbe4244fd63b69ce,

title = "Enhancing Energy Efficiency: Statistical Analysis of RRAM Operations using ZnO-based Approach",

abstract = "RRAM has garnered significant attention from various perspectives; however, certain barriers hinder its widespread adoption. These challenges revolve around reliability and power operation, making their resolution crucial. This work highlights the effects of operating at high voltages (>10V), which also affect other memory technologies, including Flash memory. The study introduces an insightful approach involving voltage flow analysis coupled with exploring the fundamental thermal energy flow in ZnO-based RRAM stacks operating within 1.2V. The model adopts a two-dimensional arrangement in COMSOL Multiphysics and further employs MATLAB (LiveLinkTM). The research delves into the dynamic resistance switching process, elucidating the role of joule heating effects, field-driven ion transport, and the temperature influence when the operating voltage exceeds 1.2V, as depicted in various plots. This investigation advances our comprehension of the complex dynamics involved in RRAM operation and demonstrates methods to enhance device performance, improve reliability, and ensure long-term functionality in practical applications.",

keywords = "Energy efficiency, RRAM operations, Simulation, ZnO-based RRAM",

author = "Bature, \{Usman Isyaku\} and \{Mohd Nawi\}, Illani and \{Md Khir\}, \{Mohd Haris\} and \{Ba Hashwan\}, \{Saeed S.\} and Furqan Zahoor and Rahman, \{Mohammad Obaidur\}",

note = "Publisher Copyright: {\textcopyright} 2023 IEEE.; 2023 IEEE International Conference on Sensors and Nanotechnology, SENNANO 2023 ; Conference date: 26-09-2023 Through 27-09-2023",

year = "2023",

doi = "10.1109/SENNANO57767.2023.10352520",

language = "English",

series = "2023 IEEE International Conference on Sensors and Nanotechnology, SENNANO 2023",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

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booktitle = "2023 IEEE International Conference on Sensors and Nanotechnology, SENNANO 2023",

address = "United States",

}

Bature, UI, Mohd Nawi, I, Md Khir, MH, Ba Hashwan, SS, Zahoor, F & Rahman, MO 2023, Enhancing Energy Efficiency: Statistical Analysis of RRAM Operations using ZnO-based Approach. in 2023 IEEE International Conference on Sensors and Nanotechnology, SENNANO 2023. 2023 IEEE International Conference on Sensors and Nanotechnology, SENNANO 2023, Institute of Electrical and Electronics Engineers Inc., pp. 150-153, 2023 IEEE International Conference on Sensors and Nanotechnology, SENNANO 2023, Putrajaya, Malaysia, 26/09/23. https://doi.org/10.1109/SENNANO57767.2023.10352520

Enhancing Energy Efficiency: Statistical Analysis of RRAM Operations using ZnO-based Approach. / Bature, Usman Isyaku; Mohd Nawi, Illani; Md Khir, Mohd Haris et al.
2023 IEEE International Conference on Sensors and Nanotechnology, SENNANO 2023. Institute of Electrical and Electronics Engineers Inc., 2023. p. 150-153 (2023 IEEE International Conference on Sensors and Nanotechnology, SENNANO 2023).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Enhancing Energy Efficiency

T2 - 2023 IEEE International Conference on Sensors and Nanotechnology, SENNANO 2023

AU - Bature, Usman Isyaku

AU - Mohd Nawi, Illani

AU - Md Khir, Mohd Haris

AU - Ba Hashwan, Saeed S.

AU - Zahoor, Furqan

AU - Rahman, Mohammad Obaidur

PY - 2023

Y1 - 2023

N2 - RRAM has garnered significant attention from various perspectives; however, certain barriers hinder its widespread adoption. These challenges revolve around reliability and power operation, making their resolution crucial. This work highlights the effects of operating at high voltages (>10V), which also affect other memory technologies, including Flash memory. The study introduces an insightful approach involving voltage flow analysis coupled with exploring the fundamental thermal energy flow in ZnO-based RRAM stacks operating within 1.2V. The model adopts a two-dimensional arrangement in COMSOL Multiphysics and further employs MATLAB (LiveLinkTM). The research delves into the dynamic resistance switching process, elucidating the role of joule heating effects, field-driven ion transport, and the temperature influence when the operating voltage exceeds 1.2V, as depicted in various plots. This investigation advances our comprehension of the complex dynamics involved in RRAM operation and demonstrates methods to enhance device performance, improve reliability, and ensure long-term functionality in practical applications.

AB - RRAM has garnered significant attention from various perspectives; however, certain barriers hinder its widespread adoption. These challenges revolve around reliability and power operation, making their resolution crucial. This work highlights the effects of operating at high voltages (>10V), which also affect other memory technologies, including Flash memory. The study introduces an insightful approach involving voltage flow analysis coupled with exploring the fundamental thermal energy flow in ZnO-based RRAM stacks operating within 1.2V. The model adopts a two-dimensional arrangement in COMSOL Multiphysics and further employs MATLAB (LiveLinkTM). The research delves into the dynamic resistance switching process, elucidating the role of joule heating effects, field-driven ion transport, and the temperature influence when the operating voltage exceeds 1.2V, as depicted in various plots. This investigation advances our comprehension of the complex dynamics involved in RRAM operation and demonstrates methods to enhance device performance, improve reliability, and ensure long-term functionality in practical applications.

KW - Energy efficiency

KW - RRAM operations

KW - Simulation

KW - ZnO-based RRAM

UR - https://www.scopus.com/pages/publications/85182747810

U2 - 10.1109/SENNANO57767.2023.10352520

DO - 10.1109/SENNANO57767.2023.10352520

M3 - Conference contribution

AN - SCOPUS:85182747810

T3 - 2023 IEEE International Conference on Sensors and Nanotechnology, SENNANO 2023

SP - 150

EP - 153

BT - 2023 IEEE International Conference on Sensors and Nanotechnology, SENNANO 2023

PB - Institute of Electrical and Electronics Engineers Inc.

Y2 - 26 September 2023 through 27 September 2023

ER -

Bature UI, Mohd Nawi I, Md Khir MH, Ba Hashwan SS, Zahoor F, Rahman MO. Enhancing Energy Efficiency: Statistical Analysis of RRAM Operations using ZnO-based Approach. In 2023 IEEE International Conference on Sensors and Nanotechnology, SENNANO 2023. Institute of Electrical and Electronics Engineers Inc. 2023. p. 150-153. (2023 IEEE International Conference on Sensors and Nanotechnology, SENNANO 2023). doi: 10.1109/SENNANO57767.2023.10352520

Enhancing Energy Efficiency: Statistical Analysis of RRAM Operations using ZnO-based Approach

Abstract

Publication series

Conference

Bibliographical note

UN SDGs

Keywords

ASJC Scopus subject areas

Access to Document

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Cite this