Sweating Rate‐Adaptive Knitted Fabric with Janus and Skin‐Like Functions
Abstract Sweat management functional clothing typically employs one‐way water transport fabrics or “skin‐like” fabrics, but achieving both functionalities simultaneously is challenging due to their distinct water transfer mechanisms. This study developed a self‐adaptive water‐transporting fabric using wool/acrylic blended yarns with different wettability, which exhibited the two functionalities. Using plasma pretreatment technology and yarn surface coating method, the controlled wettability of wool/acrylic blended yarn is achieved. Yarns with moderate‐hydrophobicity showed a 523% increase in wicking length compared to raw yarns within 270 s, while yarns with enhanced hydrophobicity exhibit superhydrophobic characteristics, with a maximum contact angle of 150° and good wash durability. The sweating rate‐adaptive knitted fabric (SRAF) demonstrates distinct water transfer behaviors at different sweating rates: at 3 mL h −1 , liquid is transported from the back to the face side and spread over a large area; at 15 mL h −1 , part of the liquid is transported to the face side and dripped off. Finally, yarn permeability is used to predict wicking length of fabric, with an error of less than 5%. The integration of theoretical modelling and finite element simulation bridged the gap between yarn‐level properties and fabric performance, offering a scalable approach for multifunctional textile development.
Authors
- Xingmin Li
- Rongfei Liu
- Peng Xu (ORCID: https://orcid.org/0000-0002-4349-5627)
- Dahua Shou (ORCID: https://orcid.org/0000-0003-3896-7885)
- Qing Chen (ORCID: https://orcid.org/0000-0002-3597-584X)
Institutions
- Hong Kong Polytechnic University (HK)
- Donghua University (CN)
- Kangmei Pharmaceutical (China) (CN)
- China Jiliang University (CN)
Publication Details
- Journal
- Advanced Functional Materials
- Published
- 2025-08-27
- DOI
- https://doi.org/10.1002/adfm.202514152
- Citations
- 1
- Primary Topic
- Advanced Materials and Mechanics
- Type
- article
- Field-Weighted Citation Impact
- 0.71
Funders
- National Natural Science Foundation of China