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Piezopotential-Programmed Multilevel Nonvolatile Memory As Triggered by Mechanical Stimuli.

Qijun Sun1, Dong Hae Ho, Yongsuk Choi

  • 1Beijing Institute of Nanoenergy and Nanosystems, Chinese Academy of Sciences, National Center for Nanoscience and Nanotechnology (NCNST), Beijing 100083, P. R. China.

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|December 10, 2016
PubMed
Summary
This summary is machine-generated.

Researchers developed a novel nonvolatile memory array using piezoelectric nanogenerators (NGs) and field-effect transistors (FETs). This piezopotential-programmed memory reduces power consumption and enables multilevel data storage for advanced electronic applications.

Keywords:
multilevel data storagenanogeneratornonvolatile memorypiezopotentialtransistor

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Area of Science:

  • Materials Science and Engineering
  • Nanoelectronics
  • Solid-State Devices

Background:

  • Conventional nonvolatile memory devices rely on gate voltage for programming/erasing operations, contributing to significant power consumption.
  • There is a growing need for low-power, high-performance memory solutions for emerging applications like electronic skin and human-robot interfaces.
  • Piezoelectric nanogenerators (NGs) offer a potential route to harvest mechanical energy and generate electrical potentials.

Purpose of the Study:

  • To develop a novel piezopotential-programmed nonvolatile memory array.
  • To integrate ion gel-gated field-effect transistors (FETs) with piezoelectric nanogenerators (NGs).
  • To demonstrate reduced power consumption and multilevel data storage capabilities.

Main Methods:

  • Fabrication of a memory array combining ion gel-gated FETs and piezoelectric NGs.
  • Utilizing piezopotentials generated by NGs under external strain to program/erase memory states.
  • Investigating multilevel data storage by varying the applied bending strain on NGs.

Main Results:

  • Achieved piezopotential-based programming/erasing, significantly reducing power consumption compared to conventional methods.
  • Demonstrated multilevel data storage capability, achieving 2 bits (over 4 levels) by controlling strain.
  • Exhibited excellent memory performance: programming/erasing current ratio > 103, stability over 100 cycles, and data retention > 3000 s.

Conclusions:

  • The developed piezopotential-programmed nonvolatile memory device offers a low-power alternative for data storage.
  • This technology is suitable for advanced applications requiring integrated sensing and memory, such as data-storable electronic skin.
  • The device shows promise for enhancing human-robot interface operations through efficient and responsive data handling.