Scalable Manufactured Self-Healing Strain Sensors Based on Ion-Intercalated Graphene Nanosheets and Interfacial Coordination
Source abstract
Abstract
Desirable mechanical strength and self-healing performance are very important to highly sensitive and stretchable sensors to meet their practical applications. However, balancing these two key performance parameters is still a great challenge. Herein, we present a simple, large-scale, and cost-efficient route to fabricate autonomously self-healing strain sensors with satisfactory mechanical properties. Specifically, ion-intercalated mechanical milling was utilized to realize the large-scale preparation of graphene nanosheets (GNs). Then, a well-organized GN-nanostructured network was constructed in a rubber matrix based on interfacial metal-ligand coordination. The resultant nanocomposites show desirable mechanical properties (∼5 times higher than that of control sample without interfacial coordination), excellent self-healing performance (even healable in various harsh conditions, for example, underwater, at subzero temperature or exposed in acidic and alkaline conditions), and ultrahigh sensitivity (gauge factor ≈ 45 573.1). The elaborately designed strain sensors offer a feasible approach for the scalable production of self-healing strain-sensing devices, making it promising for further applications, including artificial skin, smart robotics, and other electrical devices.
Source: openalex_inverted_index · Quality: baseline
Research context
OpenAlex topics: Advanced Sensor and Energy Harvesting Materials · Conducting polymers and applications · Supercapacitor Materials and Fabrication
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
State Key Laboratory of Polymer Materials and Engineering, Sichuan University, Chengdu 610065, China
Guangxi Key Laboratory of Calcium Carbonate Resources Comprehensive Utilization, College of Materials & Environmental Engineering, Hezhou University, Hezhou 542899, China
Funding
Chinese Academy of Tropical Agricultural Sciences · National Natural Science Foundation of China
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