MXene-enhanced nanofiber yarns for dual-mode sensing in wearable electronics
Abstract
Abstract Flexible strain-sensing yarns are crucial components in smart textiles. However, integrating high-performance tensile and pressure sensing into a single yarn to monitor comprehensive human activities remains a significant challenge. In this work, we present a dual-model strain-sensing nanofiber yarn fabricated by self-shrinking MXene-coated carbon black/thermoplastic polyurethane (MXene@CB/TPU) composite nanofiber films into Janus-structured slim scrolls, followed by double twisting using internal stress. Carbon black doping enables conductive nanofibers to bridge propagated cracks in MXene coating, forming a synergetic conductive network. This structure enhances the yarn’s tensile sensing linearity from 0.810 to 0.994, while achieving a broad range of 106% with a gauge factor of 56. The self-shrunk and double-twisted architecture also provides dual-stage pressure sensitivity, endowing the yarn with an ultrahigh pressure-sensing range of up to 10 MPa, a sensitivity of 17.74 MPa−1, and a linearity of 0.997 (0–3 MPa). Furthermore, the yarn exhibits excellent washability (> 30 ultrasonic washing cycles) owing to crosslinked nanofibers that protect the MXene layer. We demonstrated the practical applicability of this yarn by stitching it into various smart textiles, which successfully detected both tensile and pressure signals from full-range human activities. As a proof-of-concept, a smart waist support developed using this yarn can monitor both dynamic and static waist status. This work achieves high-performance dual tensile and pressure sensing in smart textiles using a single yarn, opening new pathways for advanced wearable electronics.
Fields of Study & Subjects
Advanced Sensor and Energy Harvesting Materials
2D Materials and Applications
Advanced Materials and Mechanics
Publication details
- Journal / source
- Nano Research
- Publisher
- Tsinghua University Press
- Volume
- 19
- Issue
- 6
- Pages
- 94908397–94908397
- Publication date
- 5 January 2026
- Language
- EN