Natural Leaf-Inspired Bionic Fabric with Self-Driven Water Sorption/Desorption Capacity for Stable Spectral and Transpiration Simulation

Abstract

Existing bionic fabrics still face challenges such as poor stability of spectral and transpiration simulation, which seriously limits their advanced camouflage application. Herein, inspired by natural leaves, a self-driven water sorption/desorption bionic polyester (PET) fabric based on a dual-network (DN) hydrogel was developed, which could achieve stable spectral and transpiration simulation. Specifically, polar hydrophilic groups on the surface of DN hydrogels could capture atmospheric water, while the internal osmotic pressure continuously transported the captured water inward and stored it through swelling, thereby dynamically refreshing the adsorption sites. This interaction enhanced the water capture capacity of the bionic fabric, thereby enabling it to effectively mimic the “water absorption valleys” for a long period (30 days). After combining the DN hydrogel with PET fabric, the bionic fabric demonstrated exceptional spectral simulation performance with a spectral correlation coefficient of 0.9908. Furthermore, the automatic sorption and desorption of atmospheric water enable accurate mimicry of leaf transpiration, achieving a smaller temperature difference between the bionic fabric and the natural leaves (≤0.9 °C). This self-driven water sorption/desorption bionic fabric addresses the long-standing issue of inferior spectral and transpiration simulation and offers new insights into the development of camouflage fabrics.

Keywords

Bionic fabric / Spectral simulation / Transpiration / Dual-network hydrogel / Water sorption/desorption

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Funding

National Natural Science Foundation of China(22475086)

Funded by Basic Research Program of Jiangsu(BK20253059)

Xiandao Pre-research Project of Wuxi Industrial Innovation Research Institute(XD24004)

Postgraduate Research & Practice Innovation Program of Jiangsu Province(KYCX24_2549)

RIGHTS & PERMISSIONS

Donghua University, Shanghai, China