Multifunctional composite as a structural supercapacitor and self-sensing sensor using NiCo2O4 nanowires and ionic liquid
Source abstract
Abstract
Abstract A novel multifunctional composite has been developed with functions of a supercapacitor and structural health monitoring sensor. The need for energy efficiency, lightweightness, and safety motivated the study for the multifunctional composite. The electrical energy storage was realized by nickel-cobaltite-grown conductive uni-directional carbon fibers (UDCFs), an aramid fiber, and an ionic liquid with a lithium-based salt as electrodes, a separator, and an electrolyte of the supercapacitor, respectively. The structural health monitoring sensor was enabled using the electrical resistance changes of the composite under mechanical loading. These functions can be utilized for the structural supercapacitor and self-sensing structure. Hence, the composite is called a 2-in-1 multifunctional composite. The nickel cobaltite nanowire and ionic liquid exhibited promising energy storage capacitance (37.43 F g−1) as a structural supercapacitor. Moreover, its energy density and power density were 176.37 mWh kg−1 and 36.96 W kg−1, respectively. The UDCF exhibited a clear electromechanical behavior. Therefore, the electrical resistance of the composite indicates an applied mechanical deformation, similar to that observed in a deformation sensor. The difference in electromechanical sensitivity with respect to the loading direction was investigated considering the orthotropic composition of the composite. The developed 2-in-1 multifunctional composite exhibits advantages of lightweightness, high energy storage, self-sensing, and facile engineering design and, thus, can be applied in various fields such as automobiles, aerospace, civil infrastructure, and industrial plants.
Source: openaire · Quality: candidate unverified · Source record ↗
Research context
OpenAlex topics: Supercapacitor Materials and Fabrication · Advanced Sensor and Energy Harvesting Materials · Conducting polymers and applications
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
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