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

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), whi...

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Bibliographic Details
Published in2023 IEEE International Conference on Sensors and Nanotechnology (SENNANO) pp. 150 - 153
Main Authors Bature, Usman Isyaku, Mohd Nawi, Illani, Md Khir, Mohd Haris, Ba Hashwan, Saeed S., Zahoor, Furqan, Rahman, Mohammad Obaidur
Format Conference Proceeding
LanguageEnglish
Published IEEE 26.09.2023
Subjects
Energy efficiency
Resistance
RRAM operations
Sensors
Simulation
Statistical analysis
Switches
Temperature
Temperature sensors
Voltage
ZnO-based RRAM
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Summary: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.
DOI:10.1109/SENNANO57767.2023.10352520