Exploitation of the tunneling effect for the development of self-sensing nanocomposite materials
Source abstract
Abstract
• The Expanded Graphite (EG) improves the Nylon electrical properties. • EG-composites are sensitive to mechanical stress, temperature, and water sorption. • Non-destructive electrical measurements can detect microscale permanent strains. • Excellent reproducibility of the signal during temperature cyclic tests is found. • The sensing water functionality can be restored by the internal joule effect. Graphite-based nanocomposites made of nylon 6 with multiple self-responsive properties have been successfully developed. A graphite percentage of 20% by weight was selected to evaluate the electrical response to external stimuli such as mechanical stress, temperature, and humidity. The strain, temperature, and water uptake sensing follow an exponential pattern in response to different external stimuli. The strain and water uptake sensing analyses yielded sensitivity values in terms of Gauge Factor (G.F.) and humidity sensitivity (β) of 62 and 16, respectively. The temperature sensitivity was estimated at 0.175%/°C within a temperature range of 20 to 80 °C. Loading-unloading cycles confirmed the capability to detect potential damage in the plastic regime. The excellent reproducibility of the signal during cyclic temperature tests suggests that the composite is suitable as a stable resistor. Additionally, cyclic tests for water adsorption and desorption indicate that the sample can regenerate without undergoing plasticization. Given the reproducibility of these tests, this technology can be applied to develop lightweight, multi-sensor devices suitable for various applications. The peculiar electrical response of the composite to various types of external stimuli is attributable to the tunneling effect.
Source: openalex_inverted_index · Quality: baseline
Research context
OpenAlex topics: Gas Sensing Nanomaterials and Sensors · Advanced Chemical Sensor Technologies · Analytical Chemistry and Sensors
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
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