Autonomous self-healing and stretchable triboelectric nanogenerator with hybrid double-network elastomer for self-powered multifunctional electronics

Research output: Contribution to journalArticlepeer-review

Abstract

Despite the widespread interest in triboelectric nanogenerators (TENGs) for self-powered wearable electronics, the development of TENGs that effectively combine self-healing and robust mechanical properties remains challenging. Herein, we report an autonomous fully self-healing TENG (SH − TENG) with excellent mechanical properties for multifunctional self-powered applications. The SH − TENG is fabricated using a self-healing Ecoflex (SH − Ecoflex) synthesized through the polymerization of an Ecoflex–polyborosiloxane (PBS) hybrid double network elastomer. The SH − Ecoflex exhibits high tensile strength, exceptional stretchability (590%), and autonomous mechanical self-healing efficiency (68% in 2 h). The SH − TENG efficiently harvests mechanical energy (269.1 mW/m2), autonomously recovers its performance even after damage or mechanical deformation, and maintains durable performance over 12,000 contact-separation cycles. The SH − TENG effectively charges the capacitor within a short time to power the digital thermo-hygrometer, and offers self-powered sensing functionality to monitor human joint movements. Furthermore, the handwriting touch panel is designed with a diagonal strip-void electrode-based SH − TENG to enhance the perception of finger sliding and generate a distinct electrical signal for each handwritten letter. Through the integration of a deep learning model, an advanced handwriting recognition system has been developed to recognize five handwritten letters with an average accuracy of 99%, demonstrating its potential for future applications in intelligent tactile perception and human–machine interaction, as well as signature and user recognition systems.

Original languageEnglish
Article number389
JournalAdvanced Composites and Hybrid Materials
Volume8
Issue number5
DOIs
StatePublished - Oct 2025

Keywords

  • Deep learning
  • Double network elastomer
  • Handwriting recognition
  • Self-healing Ecoflex
  • Self-healing TENG

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