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Integrated Memory Devices Based on 2D Materials.

Fei Xue1,2,3, Chenhui Zhang1, Yinchang Ma1

  • 1Physical Science and Engineering Division, King Abdullah University of Science and Technology, Thuwal, 23955-6900, Saudi Arabia.

Advanced Materials (Deerfield Beach, Fla.)
|May 13, 2022
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Summary
This summary is machine-generated.

Advanced 2D materials are revolutionizing memory device arrays for big data processing, offering high speed and low energy consumption. These materials enable novel brain-inspired computing and sensing applications.

Keywords:
integrated circuitsmemory devicesneuromorphic computingvan der Waals materials

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Area of Science:

  • Materials Science
  • Computer Engineering
  • Nanotechnology

Background:

  • The Internet of Things and big data necessitate memory hardware with high speed, low energy consumption, and high integration density.
  • Traditional memory technologies face limitations in meeting these stringent demands for rapid data processing and storage.
  • Two-dimensional (2D) materials offer promising electronic properties for next-generation memory devices.

Purpose of the Study:

  • To survey recent advancements in 2D material-based memory device arrays.
  • To explore the implications of these devices for brain-inspired computing and sensing.
  • To discuss current challenges and future research directions in the field.

Main Methods:

  • Review of existing literature on 2D material memory devices.
  • Analysis of various working mechanisms (defects, filaments, charges, ferroelectricity, spins).
  • Investigation of array-level integration and performance.

Main Results:

  • 2D materials enable high-performance memory arrays with desirable downscaling capabilities.
  • Various working mechanisms in 2D material devices facilitate diverse functionalities.
  • These arrays show potential for implementing advanced brain-inspired computing and sensing.

Conclusions:

  • 2D material-based memory arrays are crucial for future high-performance computing and data storage.
  • Further research is needed to address array-level challenges for practical applications.
  • The field holds significant promise for innovative computing architectures and functionalities.