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

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. • The first all-aerogel TENG, featuring superior elasticity, high output performance, and ultralow density, was successfully developed. • The mechanism of β-phase content in PVDF on enhancing triboelectric properties was systematically investigated through theoretical and experimental studies. • A self-powered wireless fencing system utilizing CNN algorithm was developed for precise, flexible competition and training insights.