Graphene-Based Triboelectric Multi-Sensors for Self-Powered Multimodal Motion Sensing in Smart Textiles
The increasing demand for real-time motion tracking in rehabilitation, athletic training, and health monitoring highlights the need for wearable sensors that are accurate, energy-efficient, and comfortable to use. Triboelectric nanogenerators (TENGs) offer a promising route by converting biomechanical activity directly into electrical signals, but their deployment is limited by mechanical instability under deformation and reliance on wired data acquisition. Here, we present a fully integrated, wireless triboelectric sensing system built on a durable textile architecture. The system employs six PDMS-based sensors enhanced with graphene nanoplatelet (GNP) conductive adhesives and connected through a miniaturized Bluetooth Low Energy (BLE) module for multichannel, real-time transmission. Among the tested formulations, a 20 wt % GNP composite achieved optimal conductivity (∼15 Ω/□) and stable signal output under repeated loading. The integrated system demonstrated voltage outputs up to 37 V during benchtop testing and maintained stability across a wide temperature range (10–50 °C). By combining scalable materials, robust sensor design, and low-power wireless communication, this work establishes a practical platform for self-powered, high-fidelity biomechanical monitoring. The proposed approach advances the pathway toward next-generation wearable systems for clinical rehabilitation and everyday health applications.
Authors
- Ismael Domingos (ORCID: https://orcid.org/0000-0003-2966-9536)
- H. Alves (ORCID: https://orcid.org/0000-0002-2971-9241)
- Cristina Antunes (ORCID: https://orcid.org/0000-0002-5934-388X)
Institutions
- University of Lisbon (PT)
- Instituto de Engenharia de Sistemas e Computadores Microsistemas e Nanotecnologias (PT)
- Instituto Superior Técnico (PT)
Publication Details
- Journal
- ACS Applied Electronic Materials
- Published
- 2025-09-24
- DOI
- https://doi.org/10.1021/acsaelm.5c01519
- Primary Topic
- Advanced Sensor and Energy Harvesting Materials
- Type
- article
- Field-Weighted Citation Impact
- 0.00