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A Review on Multi-Level Asymmetric Design for 2D Neuromorphic Devices.

Yilin Sun1, Yuandong Gao2, Zimu Wang2

  • 1School of Microelectronics Science and Technology, Sun Yat-sen University, Zhuhai, 519000, Guangdong, People's Republic of China. sunylin7@mail.sysu.edu.cn.

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This summary is machine-generated.

Asymmetry in materials, structures, and devices is key for neuromorphic computing. Engineering multi-level asymmetry in two-dimensional (2D) materials offers a pathway to advanced neuromorphic hardware.

Keywords:
Anisotropic crystal structureAsymmetric designBand alignment engineeringContact engineeringNeuromorphic devices

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Area of Science:

  • Materials Science
  • Neuroscience
  • Electrical Engineering

Background:

  • Asymmetry is a crucial design strategy for neuromorphic functionalities like directional signal propagation and synaptic plasticity.
  • Breaking symmetry introduces physical phenomena vital for emulating neurons and synapses.
  • A systematic understanding of asymmetry's function across design levels is needed.

Purpose of the Study:

  • To systematically review asymmetric engineering in materials, structures, and devices for neuromorphic applications.
  • To analyze how multi-level asymmetry in two-dimensional (2D) materials enables synaptic plasticity emulation.
  • To provide a design framework for next-generation neuromorphic hardware.

Main Methods:

  • Systematic review of asymmetric engineering across material, structural, and device levels.
  • Analysis of two-dimensional (2D) materials' properties for neuromorphic device applications.
  • Discussion of challenges and future perspectives in asymmetric neuromorphic hardware design.

Main Results:

  • Asymmetric engineering at material, structural, and device levels leads to unique physical phenomena.
  • Two-dimensional (2D) materials exhibit versatility for creating multi-level asymmetry.
  • Multi-level asymmetry in 2D materials allows for diverse and tunable neuromorphic device functions, particularly in synaptic plasticity emulation.

Conclusions:

  • Multi-level asymmetric engineering, especially with 2D materials, is a promising approach for neuromorphic computing.
  • Further research into integrating multiple asymmetries and extending to circuit/system levels is warranted.
  • This review establishes a design framework for developing advanced neuromorphic intelligent hardware.