High mechanical properties and excellent anisotropy of dually synergistic network wood fiber gel for human–computer interactive sensors

• Published in: Cellulose (London) Vol. 29; no. 8; pp. 4495 - 4508
• Main Authors: Han, Xuewen, Han, Xiaoshuai, Wang, Zhenxing, Wang, Sijie, Meng, Wanyao, Lv, Haifeng, Zhou, Zijing, Pu, Junwen
• Format: Journal Article
• Language: English
• Published: Dordrecht Springer Netherlands 01-05-2022; Springer Nature B.V
• Subjects: Anisotropy; Bioorganic Chemistry; Ceramics; Chemistry; Chemistry and Materials Science; Composites; Concrete construction; Concrete structures; Construction engineering; Glass; Ion currents; Mechanical properties; Modulus of elasticity; Natural Materials; Organic Chemistry; Original Research; Physical Chemistry; Polyacrylic acid; Polymer Sciences; Prepolymers; Reinforced concrete; Sensors; Sustainable Development; Tensile strength; Wood fibers; Gel polymerization; Conduct electricity; Piezoresistive sensors; Wood fiber
• ISSN: 0969-0239; 1572-882X
• DOI: 10.1007/s10570-022-04554-1

The development of multifunctional gel materials based on fiber is the focus of study. However, creating fiber gel materials with high mechanical properties remains challenging. Inspired by the reinforced concrete structures in construction engineering, we impregnated poly propionamide/polyacrylic acid gel prepolymer solution into the wood by vacuum and polymerized it with wood fiber in situ. The wood fiber gel (WFG) with a dually synergistic network was developed with high tensile strength, high elasticity, and excellent anisotropy. For example, the tensile strength and tensile modulus of WFG reached 7.09 MPa and 59.2 MPa, respectively. Remarkably, its compression elasticity reached 50%. Meanwhile, the ionic conductivity of WFG was 2.75 s/m, which provided more application prospects for self-insulating wood. Additionally, we used WFG to fabricate piezoresistive sensors, that maintained good pressure sensing performance after 1000 pressure responses which provided a possibility for using WFG in the fields of intelligent human–computer interaction sensors.