Passive Chips-in-Yarn Integration for On-Fabric Batteryless Identification and Sensing
Rattachement africain : cn, hk, gb. Niveau de preuve : code pays fourni par la source.
Le résumé fourni par la source
Smart clothing has the potential to monitor the body continuously, but most current systems still rely on rigid electronic modules, batteries, and wired connections. These components reduce flexibility, comfort, washability, and long-term usability. Here, we report a passive chips-in-yarn strategy for creating battery-free electronic yarns that can be integrated directly into fabrics. In this approach, radio frequency identification (RFID) chips are embedded inside yarn structures, allowing the yarns to be wirelessly powered and read by an external RFID reader without onboard batteries. The RFID chip is connected to conductive filaments that act as yarn-shaped antennas, while local encapsulation and a braided sheath protect the chip–filament junction during textile manufacturing and use. By engineering different antenna geometries, RFID yarns enable multiple functions: ID-only yarns for garment life-cycle identification, deformation-sensitive yarns for passive movement monitoring through wireless signal changes, and temperature-sensing yarns for distributed on-body thermal mapping. The resulting RFID yarns showed mechanical robustness, wash durability, and compatibility with textile weaving integration. With multiple chip-enabled yarns embedded into garments, this work demonstrates a fabric-scale sensing network that is lightweight, battery-free, and maintenance-free. This work advances smart textiles from module-attached wearable devices toward textile-native sensing systems, where passive electronic functions are embedded directly within the yarn structure. Graphical Abstract
Ce résumé expose les affirmations des auteurs. BNTIC ne l’interprète pas comme une validation indépendante des résultats.
Le contrôle bibliographique ouvert
DOI retrouvé dans Crossref DOI retrouvé ; titre concordant.
- Titre Crossref
- Passive Chips-in-Yarn Integration for On-Fabric Batteryless Identification and Sensing
- Date Crossref
- 28/08/2026
- Éditeur
- Springer Science and Business Media LLC
- Type
- journal-article
Ce recoupement confirme des métadonnées liées au DOI. Il ne confirme ni la méthode ni les conclusions de l’étude, et il ne compte pas comme une seconde source scientifique indépendante.
Les institutions déclarées
Une affiliation ne permet pas de déduire la nationalité d’un auteur.