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Self-Powered Artificial Neuron Devices: Towards the All-In-One Perception and Computation System
Tong Zheng1, Xinkai Xie1, Qiongfeng Shi1
1College of Electrical Science and Engineering, Southeast university, Nanjing, 210000, China.
Advanced Materials (Deerfield Beach, Fla.)
|February 19, 2025
Summary
This review explores self-powered artificial neuron devices using triboelectric, piezoelectric, and photoelectric effects. Integrating these with neuromorphic computation offers efficient, all-in-one systems for intelligent applications.
Area of Science:
- Materials Science
- Neuroscience
- Electrical Engineering
Background:
- Growing demand for energy-efficient sensing and computation.
- Self-powered sensing and neuromorphic computing offer solutions for low-energy, high-performance systems.
- Integration of these technologies promises all-in-one, intelligent devices.
Purpose of the Study:
- To review advancements in self-powered artificial neuron devices.
- To analyze devices based on triboelectric, piezoelectric, and photoelectric effects.
- To summarize integrated perception-computing-actuation systems.
Main Methods:
- Examination of device structures, mechanisms, and functions.
- Comparison of electrical characteristics of various self-powered artificial neuron devices.
- Discussion of performance enhancement strategies.
Main Results:
- Overview of self-powered artificial neuron devices utilizing different physical effects.
- Summary of self-powered perception systems (tactile, visual, auditory).
- Elucidation of integrated systems for closed-loop control.
Conclusions:
- Self-powered sensing and neuromorphic computation integration is a promising approach.
- These integrated systems pave the way for advanced, intelligent applications.
- Further development holds potential for a more intelligent future.
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The receptor level:
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