Highly elastic, lightweight, and high-performance all-aerogel triboelectric nanogenerator for self-powered intelligent fencing training

作者：Muqi Chen, Min Ji, Lijun Huang, Ningxiang Wu, Tao Jiang, Chengyu Li, Wanpeng Li, Boyang Yu, Jianjun Luo, Xiaoyi Li, Zhong Lin Wang · 发表于：Materials Science and Engineering R Reports · 年份：2025 · DOI：10.1016/j.mser.2025.101004 · 被引用次数：46 · 研究领域：Advanced Sensor and Energy Harvesting Materials、Conducting polymers and applications、Tactile and Sensory Interactions

With the rapid advancement of the Internet of Things and big data , the sports industry is undergoing a digital transformation. Here, we report a highly elastic, lightweight, and high-performance all-aerogel triboelectric nanogenerator (AA-TENG) for self-powered sensing in intelligent fencing training. Utilizing simple yet effective freeze-drying strategies for fabricating cellulose/carbon nanotube and poly(vinylidene fluoride-co-trifluoroethylene) (PVDF-TrFE) aerogels, the resulting AA-TENG demonstrates an ultralow density of 7.92 × 10 −3 g/cm 3 , exceptional elasticity (≥90 % height retention) and thermal insulation performance. Moreover, the electrical output performance is significantly enhanced by 57 %, attributed to the increased β-phase content (88.95 %) in the PVDF-TrFE aerogel . Furthermore, a self-powered wireless fencing strike analysis system using convolutional neural network algorithm is developed to accurately classify three types of fencing strikes, enabling more flexible and precise competition judgment and training analysis. This work provides new insights into the application of self-powered systems in intelligent sports and big data analysis, with the potential to significantly impact the global sports industry.