Flexible High Temperature Stable Hydrogel Based Triboelectric Nanogenerator for Structural Health Monitoring and Deep Learning Augmented Human Motion Classification

Abstract

Triboelectric nanogenerators (TENGs) are an emerging technology that harvests abundant vibrational energy present in ambient environment. TENGs typically rely on polymer contact interfaces, which, while ideal for wearable and flexible applications, limit their applicability in industry settings, where high-temperature plant equipment generates plentiful and wasted vibrational energy. In this study, a biocompatible PDMS-hydrogel nanocomposite TENG is fabricated, containing nanoparticles of ZnAl-layered double hydroxide (LDH). This device demonstrates a maximum power density of 110 µW cm⁻², and nanocomposite-based TENG shows exceptional stability in terms of output voltage up to 200 °C, making it suitable for harvesting waste vibrational energy from high-temperature industrial equipment. The fabricated TENG demonstrates its potential for structural health monitoring by exhibiting distinct energy spectral changes under different wave input excitations (sinusoidal, square, and triangular) at the same frequency, signifying its potential for vibration analysis of industrial machines. With its high-temperature functionality, the device remains applicable for wearable energy harvesting and human motion monitoring, ideal for monitoring in high-temperature environments. Here, this is demonstrated via a deep learning model for classification of human motions using the TENG voltage waveforms. The combination of high-temperature stability and wearable motion monitoring enables future industrial energy harvesting and extreme environment personnel monitoring.