JOURNAL ARTICLE

Triboelectric nanogenerator for neuromorphic electronics

Abstract

Building the brain-inspired neural network computing system based neuromorphic electronics is an effective approach to break the von Neumann bottleneck on the hardware level and realize the information processing with high efficiency and low energy consumption in this big data explosion age. Triboelectric nanogenerator (TENG) has two functions of sensing and energy conversion, which promote the application as sensor and/or power supply in self-powered neuromorphic electronics for data storage and biological synapse/neuron behaviors mimicking. This article highlights the relevant works of TENGs for memory devices, artificial synapses and artificial neurons, performs a systematic comparison, and puts forward the future research possibilities and challenges, with the hope of attracting more researchers into this field and promoting the development of TENG based neuromorphic electronics.

Keywords:
Neuromorphic engineering Triboelectric effect Electronics Bottleneck Von Neumann architecture Computer science Efficient energy use Artificial neural network Artificial intelligence Engineering Electrical engineering Embedded system Materials science

Metrics

25
Cited By
3.97
FWCI (Field Weighted Citation Impact)
161
Refs
0.91
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Advanced Sensor and Energy Harvesting Materials
Physical Sciences →  Engineering →  Biomedical Engineering
Advanced Memory and Neural Computing
Physical Sciences →  Engineering →  Electrical and Electronic Engineering
Conducting polymers and applications
Physical Sciences →  Materials Science →  Polymers and Plastics
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