Mechano-intelligent Auxetic Triboelectric Textiles for Enhanced Energy Harvesting and AI-Driven Gesture Recognition

Yuanyuan Gao , Zhenyu Li , Minyu Qiu , Taosif Ahmed , Tingyi Yin , Xiangkun Bo , King Yan Chung , Hong Hu , Hong Fu , Bingang Xu

Advanced Fiber Materials ›› : 1 -15.

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Advanced Fiber Materials ›› :1 -15. DOI: 10.1007/s42765-026-00730-1
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Mechano-intelligent Auxetic Triboelectric Textiles for Enhanced Energy Harvesting and AI-Driven Gesture Recognition
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Abstract

The advancement of wearable electronics, especially smart clothing, is limited by the rigidity and bulkiness of conventional power sources, highlighting the need for sustainable energy solutions. Textile-based triboelectric nanogenerators (T-TENGs) offer a promising approach for harvesting biomechanical energy and enabling self-powered sensing. However, traditional planar or simple 3D T-TENG structures often struggle to adapt efficiently to complex human motions, resulting in reduced electrical output and stability. In this study, we present a mechano-intelligent auxetic triboelectric textile (MIA-TENG) that integrates auxetic structures into the fabric to actively enhance contact and separation dynamics at the triboelectric interface. The MIA-TENG, fabricated from a composite of polydimethylsiloxane (PDMS) and nylon fabric, leverages the negative Poisson’s ratio effect of auxetic structures to enhance output performance with wearing comfort. Experimental results show that the MIA-TENG achieves a peak power output of 3610 mW m−2 and maintains excellent durability and washability, with a stable performance after 10 washing cycles and 60,000 mechanical tests. The device can power portable electronics and is suitable for both large-joint protection and high-fidelity gesture sensing. Combined with machine learning algorithms, the system enables accurate gesture recognition, offering an integrated platform for advanced applications in motion capture, health monitoring, and smart sports.

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Mechano-intelligent textile / Auxetic structure / Energy harvesting / Self-powered sensing / Gesture recognition / Machine learning

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Yuanyuan Gao, Zhenyu Li, Minyu Qiu, Taosif Ahmed, Tingyi Yin, Xiangkun Bo, King Yan Chung, Hong Hu, Hong Fu, Bingang Xu. Mechano-intelligent Auxetic Triboelectric Textiles for Enhanced Energy Harvesting and AI-Driven Gesture Recognition. Advanced Fiber Materials 1-15 DOI:10.1007/s42765-026-00730-1

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Hong Kong Polytechnic University(1-BBH6)

The Hong Kong Polytechnic University

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