Toughening Eutectic Gels by Muscle‐Like Training

ABSTRACT Double‐network (DN) gels have been demonstrated to possess enhanced toughness and fatigue resistance when compared to their single‐network counterparts. Nevertheless, these gels lack the specific directional orientation inherent in the anisotropic ordered structures characteristic of natural materials, thereby restricting their applicability within the domain of biomimetics. Herein, inspired by muscle stretching, we propose a facile strategy to prepare a single‐network anisotropic eutectic gel through an innovative approach that integrates solution replacement with circuit mechanical training. This strategy mimics the mechanism of muscle strengthening to form comprehensively reinforced gel muscles and skins for soft robots. The resultant gels exhibit unexceptionable mechanical and electrical properties compared to conventional single‐network gels, surpassing even the performance metrics of DN gels. Attributable to the anisotropic nanofibrous structures, which incorporate crystalline polymer frameworks and a high density of hydrogen bonds, these gels exhibit comprehensive mechanical properties of high strength (> 8.5 MPa), high toughness (∼20 MJ/m 3 ), and high fatigue resistance (> 1100 J/m 2 ), and also resistance to drying and freezing. Additionally, upon eutectic liquid infusion, these gels achieve a high electrical conductivity (∼350 mS/m) and display sensitivity to temperature, strain, and pressure variations. Such properties position the toughened gel as a highly promising candidate for actuators and sensors in soft robotics, enabling high‐output actuation and multi‐modal sensing integration.

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Publication Details

Journal
SmartBot
Published
2025-11-29
DOI
https://doi.org/10.1002/smb2.70016
Citations
1
Primary Topic
Advanced Sensor and Energy Harvesting Materials
Type
article
Field-Weighted Citation Impact
0.67

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article

Toughening Eutectic Gels by Muscle‐Like Training

Hao Ma, Jing Xiong, Zeyang Xia, Jing Wang et al.
1 citations
SmartBot
Advanced Sensor and Energy Harvesting Materials
0.67
article

Toughening Eutectic Gels by Muscle‐Like Training

Hao Ma, Jing Xiong, Zeyang Xia, Jing Wang, Ming Li, Jian Chen
article en
1 citations

Abstract

ABSTRACT Double‐network (DN) gels have been demonstrated to possess enhanced toughness and fatigue resistance when compared to their single‐network counterparts. Nevertheless, these gels lack the specific directional orientation inherent in the anisotropic ordered structures characteristic of natural materials, thereby restricting their applicability within the domain of biomimetics. Herein, inspired by muscle stretching, we propose a facile strategy to prepare a single‐network anisotropic eutectic gel through an innovative approach that integrates solution replacement with circuit mechanical training. This strategy mimics the mechanism of muscle strengthening to form comprehensively reinforced gel muscles and skins for soft robots. The resultant gels exhibit unexceptionable mechanical and electrical properties compared to conventional single‐network gels, surpassing even the performance metrics of DN gels. Attributable to the anisotropic nanofibrous structures, which incorporate crystalline polymer frameworks and a high density of hydrogen bonds, these gels exhibit comprehensive mechanical properties of high strength (> 8.5 MPa), high toughness (∼20 MJ/m 3 ), and high fatigue resistance (> 1100 J/m 2 ), and also resistance to drying and freezing. Additionally, upon eutectic liquid infusion, these gels achieve a high electrical conductivity (∼350 mS/m) and display sensitivity to temperature, strain, and pressure variations. Such properties position the toughened gel as a highly promising candidate for actuators and sensors in soft robotics, enabling high‐output actuation and multi‐modal sensing integration.

SmartBotVol. 1(4)
Shanghai Jiao Tong University (CN), Shenzhen Institutes of Advanced Technology (CN)
National Natural Science Foundation of China, Chinese Academy of Sciences, Shanghai Jiao Tong University, Youth Innovation Promotion Association, Basic and Applied Basic Research Foundation of Guangdong Province
Openalex Percentile: Top 24%
Advanced Sensor and Energy Harvesting Materials
0.67
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