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Artificial Neuronal Devices Based on Emerging Materials: Neuronal Dynamics and Applications.

Hefei Liu1, Yuan Qin2, Hung-Yu Chen1

  • 1Ming Hsieh Department of Electrical and Computer Engineering, University of Southern California, Los Angeles, CA, 90089, USA.

Advanced Materials (Deerfield Beach, Fla.)
|January 7, 2023
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Summary

Artificial neuronal devices mimic brain functions for neuromorphic computing. This review covers devices using volatile materials, focusing on their neuron models, functions, and applications.

Keywords:
artificial neuronsbrain emulationneuromorphic computingsensory neuronsspiking neural networks

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Area of Science:

  • Materials Science
  • Neuroscience
  • Computer Engineering

Background:

  • Neuromorphic computing systems require artificial neuronal devices.
  • Existing devices mimic neuronal dynamics but vary in structure and physics.
  • Volatile switching materials offer a promising avenue for artificial neuron development.

Purpose of the Study:

  • To review artificial neuronal devices based on volatile switching materials.
  • To analyze implemented neuronal functions and their applications.
  • To discuss future directions for enhancing artificial neuron capabilities.

Main Methods:

  • Literature review of artificial neuronal devices.
  • Analysis of device behavior through established neuron models.
  • Focus on volatile switching materials and their properties.

Main Results:

  • Various artificial neuronal devices exhibit distinct neuron models.
  • Implemented neuronal functions are explored for computational and sensing tasks.
  • Volatile materials enable diverse artificial neuron functionalities.

Conclusions:

  • Artificial neuronal devices show potential for advanced computing and brain emulation.
  • Further research is needed to incorporate more complex neuronal dynamics.
  • Neuroscience-inspired designs can lead to more functional artificial neurons.