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

IF 31.6 1区材料科学 Q1 MATERIALS SCIENCE, MULTIDISCIPLINARY

Materials Science and Engineering: R: Reports Pub Date : 2025-04-30 DOI:10.1016/j.mser.2025.101004

Muqi Chen , Minglan Ji , Lijun Huang , Ning Wu , Tao Jiang , Chengyu Li , Wanpeng Li , Boyang Yu , Jianjun Luo , Xiaoyi Li , Zhong Lin Wang

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引用次数: 0

Abstract

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 × 10⁻³g/cm³, 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.

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高弹性，轻质，高性能的全气凝胶摩擦电纳米发电机，用于自供电智能击剑训练

随着物联网和大数据的快速发展，体育产业正在经历一场数字化转型。在这里，我们报道了一种高弹性、轻质、高性能的全气凝胶摩擦电纳米发电机（AA-TENG），用于智能击剑训练中的自供电传感。利用简单而有效的冷冻干燥策略来制造纤维素/碳纳米管和聚（聚氟乙烯-共三氟乙烯）（PVDF-TrFE）气凝胶，得到的aaa - teng具有7.92 × 10−3g/cm3的超低密度，优异的弹性（≥90 %高度保持）和隔热性能。此外，由于PVDF-TrFE气凝胶中β相含量（88.95 %）的增加，电输出性能显著提高了57 %。在此基础上，开发了一种基于卷积神经网络算法的自供电无线击剑击球分析系统，对击剑三种击球类型进行准确分类，使比赛判断和训练分析更加灵活和精确。这项工作为自供电系统在智能体育和大数据分析中的应用提供了新的见解，有可能对全球体育产业产生重大影响。

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来源期刊

Materials Science and Engineering: R: Reports 工程技术-材料科学：综合

CiteScore

60.50

自引率

0.30%

发文量

审稿时长

34 days

期刊介绍： Materials Science & Engineering R: Reports is a journal that covers a wide range of topics in the field of materials science and engineering. It publishes both experimental and theoretical research papers, providing background information and critical assessments on various topics. The journal aims to publish high-quality and novel research papers and reviews. The subject areas covered by the journal include Materials Science (General), Electronic Materials, Optical Materials, and Magnetic Materials. In addition to regular issues, the journal also publishes special issues on key themes in the field of materials science, including Energy Materials, Materials for Health, Materials Discovery, Innovation for High Value Manufacturing, and Sustainable Materials development.