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Related Experiment Video

Updated: Nov 2, 2025

Design and Characterization Methodology for Efficient Wide Range Tunable MEMS Filters

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Published on: February 4, 2018

Multilevel resistive random access memory achieved by MoO₃/Hf/MoO₃stack and its application in tunable high-pass

Sheng Li Fang¹, Chuan Yu Han¹, Wei Hua Liu¹

¹School of Microelectronics, Faculty of Electronics and Information Engineering, Xi'an Jiaotong University, Xi'an 710049, People's Republic of China.

|June 11, 2021

Summary

Multilevel resistive random access memories (RRAMs) with four stable states were developed. These RRAMs enable tunable high-pass filters, showing potential for advanced neural networks and low-power electronics.

Keywords:

MoO3 multilevel RRAM retention property tunable high-pass filter

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Area of Science:

Materials Science
Electrical Engineering
Nanotechnology

Background:

Resistive random access memories (RRAMs) are promising for next-generation electronic devices.
Achieving multilevel resistance states is crucial for higher data storage density and complex functionalities.
Tunable filters are essential components in various electronic systems.

Purpose of the Study:

To develop and characterize multilevel RRAM devices with multiple stable resistance states.
To investigate the resistive switching mechanism in the fabricated RRAM structure.
To demonstrate the application of these multilevel RRAMs in creating tunable high-pass filters.

Main Methods:

Fabrication of Pt/MoO3/Hf/MoO3/Pt stack for multilevel RRAM.
Experimental characterization of device performance, including retention and memory window.
Electrical analysis using current-voltage (I-V) measurements and fitting to conduction models (Poole-Frenkel, Ohmic).
Simulation of device behavior and RRAM-based tunable high-pass filter (HPF).

Main Results:

Achieved RRAM devices with four stable resistance states and good retention (>10^4 s).
Demonstrated a large memory window (>10^4) for the multilevel RRAMs.
Identified the switching mechanism as a combination of conductive filament formation and redox reactions.
Conduction mechanisms identified as Poole-Frenkel emission (HRS) and Ohmic conduction (LRS).
Successfully realized a tunable high-pass filter with configurable characteristics using the multilevel RRAMs.

Conclusions:

The developed multilevel RRAMs exhibit excellent performance characteristics.
The understanding of the resistive switching mechanism provides insights for further device optimization.
The successful implementation of tunable HPFs highlights the potential of these RRAMs for applications in spiking neural networks and compact, low-power electronic filters.