A 3D-printed acoustic triboelectric nanogenerator for quarter-wavelength acoustic energy harvesting and self-powered edge sensing

Low-frequency acoustic energy harvesting is of great significance in the academic field and industry. In this work, we propose a 3D-printed acoustic triboelectric nanogenerator (A-TENG) with the properties of structural controllability, one-time molding, easy fabrication, and low cost. A quarter-wavelength acoustic resonator system based on the A-TENG is demonstrated and systemically investigated for high-performance acoustic energy scavenging. The system is capable of generating a power output of 4.33 mW under 100 dB sound pressure level excitation. Up to 72 LEDs and a commercial calculator can be directly and continuously driven by the acoustic resonator system, indicating its application as a power source for electronic devices. Furthermore, we develop a self-powered edge sensing system consisting of the A-TENG, an AI speech recognition chip, and control circuits. The speech signals can be firstly converted into electrical signals through the A-TENG, and then recognized and processed by the AI chip with a built-in and pre-trained neural network to control the follow-up circuits. The selfpowered edge sensing system is capable of real-time speech recognition without cloud computing, exhibiting great potential in the field of low-power and cost-effective intelligent Internet of Things.

Automated summary

This work introduces a 3D-printed acoustic triboelectric nanogenerator for high-performance energy harvesting, capable of driving LEDs and calculators. Additionally, a self-powered edge sensing system is developed for real-time speech recognition, demonstrating great potential in the field of low-power and cost-effective intelligent Internet of Things.