Wavy-Interlocked Stretchable Triboelectric Nanogenerators Enhanced by Liquid Metal Microflowers for Self-Powered Wearable Motion Monitoring

Qianqian Xu, Yahui Meng, Yimeng He, Senfeng Zhao, Jianxun Zhang, Kechao Zhou, Yan Zhang, Peiqiong Zhou, Peiqiong Zhou, Chris Bowen, Huimin Li, Xinke Hu

Research output: Contribution to journalArticlepeer-review

Abstract

The increasing demand for sustainable, stretchable power sources in wearable electronics has driven the development of high-performance triboelectric nanogenerators (TENGs). Despite significant progress, stretchable TENGs continue to encounter critical challenges, including insufficient charge density, unstable output performance, and degraded durability when subject to large levels of deformation, which hinder their integration into high-performance flexible wearable systems. In this work, we construct a stretchable TENG by fabricating an interlocking wavy architecture using electrically conductive eutectic gallium-indium microflowers (EGaIn MFs) embedded into optimized dielectric membranes based on poly(vinylidene fluoride-trifluoroethylene) (PVDF-TrFE) and Nylon-6 nanofibers. The multi-petaled, wrinkled microflower morphology of the resulting structure is shown to increase the specific surface area and hierarchical roughness. The electron-rich properties of the EGaIn MFs promote the formation of the β-phase in PVDF-TrFE and the γ-phase in Nylon-6, and also act as localized electrically conductive “islands” which reduce the equivalent dielectric thickness and increase the overall capacitance. Based on using membranes with an optimized EGaIn MF loading level, the triboelectric layers were patterned into an interlocked wavy architecture, which expanded the effective contact area and provided a high level of stretchability. The fabricated stretchable TENG with a 30° corrugation angle exhibited a 60% tensile strain, a peak output of 188.6 V and 31.1 µA, and a sensitivity of 3.38 V per unit strain and 0.51 µA per unit strain, respectively. Finally, the device was successfully used for real-time gesture recognition, demonstrating its potential for self-powered wearable sensing and intelligent human-machine interfaces.
Original languageEnglish
Article number e21311
JournalAdvanced Science
Early online date12 Feb 2026
DOIs
Publication statusE-pub ahead of print - 12 Feb 2026

Data Availability Statement

The data that support the findings of this study are available from the corresponding author upon reasonable request.

Funding

This paper is funded by the Hong Kong Scholars Program (No. XJ2025052), China and Science and Technology Research and Development Program Project of China Railway Group Limited (No. 2023-Major-20), Overseas Talent Introduction Project of China, Xiaomi Talent Program, Hundred Youth Talents Program of Hunan, and State Key Laboratory of Powder Metallurgy, Central South University, Changsha, China.

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