Textile‐Grade Mechanoluminescent Fibers by Continuous Wet Spinning

ABSTRACT Mechanoluminescent (ML) fibers that transduce mechanical stimuli into visible light without external power or circuitry offer a bottom‐up route toward intelligent textile systems. Despite diverse fabrication strategies, most reported ML fibers exhibit insufficient mechanical robustness and scalability, hindering their transition to textile‐grade implementation. Here, we report the first continuous wet‐spun manufacturing process for ML fibers. The composite fibers, consisting of ZnS:Mn particles homogeneously embedded within a thermoplastic polyurethane (TPU) matrix, achieve high structural and optical quality owing to improved particle dispersion via ball milling, emission tuning through Mn 2+ stoichiometry control, and synergistic optimization enabled by coordinated geometric and compositional design. The resulting fibers reach lengths up to 50 m, exhibit a tensile strength of ∼24 MPa with elongation exceeding 560%, and generate rapid luminescence (<0.3 s). They maintain stable output over hundreds of deformation‐recovery cycles, withstand repeated washing, and deliver reproducible impact emission in close agreement with finite‐element modeling, demonstrating great reliability and well‐understood stress‐light coupling mechanism. These attributes enable a successful transition into functional fabrics, enabling real‐time visualization of joint motion and external impacts through biomotion‐activated optical sensing. This work establishes a scalable and versatile route for ML textiles, opening new possibilities in wearable monitoring, rehabilitation, and safety protection.

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Publication Details

Journal
Advanced Functional Materials
Published
2026-03-09
DOI
https://doi.org/10.1002/adfm.74759
Primary Topic
Advanced Sensor and Energy Harvesting Materials
Type
article
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article

Textile‐Grade Mechanoluminescent Fibers by Continuous Wet Spinning

Changhai Yi, Sixing Xiong, Huimin Wu, Zhe Wang et al.
Advanced Functional Materials
Advanced Sensor and Energy Harvesting Materials
article

Textile‐Grade Mechanoluminescent Fibers by Continuous Wet Spinning

Changhai Yi, Sixing Xiong, Huimin Wu, Zhe Wang, Xiaohong Liao, Ying Feng, J. Wang, Huiyi Zong, Yun Deng, Xiaofang Jiang, Xiangzhe Li, Luyao Zheng, Kai Wang, Jin Qian, Xiaotian Li, Liu Liu, Zihui Liang
article en

Abstract

ABSTRACT Mechanoluminescent (ML) fibers that transduce mechanical stimuli into visible light without external power or circuitry offer a bottom‐up route toward intelligent textile systems. Despite diverse fabrication strategies, most reported ML fibers exhibit insufficient mechanical robustness and scalability, hindering their transition to textile‐grade implementation. Here, we report the first continuous wet‐spun manufacturing process for ML fibers. The composite fibers, consisting of ZnS:Mn particles homogeneously embedded within a thermoplastic polyurethane (TPU) matrix, achieve high structural and optical quality owing to improved particle dispersion via ball milling, emission tuning through Mn 2+ stoichiometry control, and synergistic optimization enabled by coordinated geometric and compositional design. The resulting fibers reach lengths up to 50 m, exhibit a tensile strength of ∼24 MPa with elongation exceeding 560%, and generate rapid luminescence (<0.3 s). They maintain stable output over hundreds of deformation‐recovery cycles, withstand repeated washing, and deliver reproducible impact emission in close agreement with finite‐element modeling, demonstrating great reliability and well‐understood stress‐light coupling mechanism. These attributes enable a successful transition into functional fabrics, enabling real‐time visualization of joint motion and external impacts through biomotion‐activated optical sensing. This work establishes a scalable and versatile route for ML textiles, opening new possibilities in wearable monitoring, rehabilitation, and safety protection.

Advanced Functional Materials
South China Normal University (CN), Changsha University (CN), Wuhan Textile University (CN), Ningbo Institute of Industrial Technology (CN), Huizhou University (CN), Nanjing University of Aeronautics and Astronautics (CN)
Openalex Percentile: Top 29%
Advanced Sensor and Energy Harvesting Materials
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