In response to the rising need for flexible and lightweight materials capable of efficient heat transport, many studies have been conducted to improve the thermal properties of polymers via nanofillers. Among the various nanofillers, carbon nanotubes (CNTs) are considered as the most promising, owing to their excellent thermal and electrical properties. Accordingly, CNT/polymer composites can be used as flexible and lightweight heat transfer materials, owing to their low density. In this study, we fabricated multi-walled CNT (MWCNT)/polymer composites with different aspect ratios to investigate their effects on electrical and thermal properties. Through a three-roll milling process, CNTs were uniformly dispersed in the polymer matrix to form a conductive network. Enhanced electrical and thermal properties were observed in MWCNT composite with a high aspect ratio as compared to those with a low aspect ratio. The thermal conductivity of composites obtained as a function of the filler content was also compared with the results of a theoretical prediction model.

Electroencephalography (EEG) captures minute electrical signals emanating from the brain. These signals are vulnerable to interference from external noise and dynamic artifacts; hence, accurately recording such signals is challenging. Although dry electrodes are convenient, their signals are of limited quality; consequently, wet electrodes are predominantly used in EEG. Therefore, developing dry electrodes for accurately and stably recording EEG signals is crucial. In this study, we developed flexible dry electrodes using polydimethylsiloxane (PDMS)/carbon-nanotube (CNT) composites with isotropically wrinkled surfaces that effectively combine the advantages of wet and dry electrodes. Adjusting the PDMS crosslinker ratio led to good adhesion, resulting in a highly adhesive CNT/PDMS composite with a low Young’s modulus that exhibited excellent electrical and mechanical properties owing to its ability to conformally contact skin. The isotropically wrinkled surface also effectively controls dynamic artifacts during EEG signal detection and ensures accurate signal analysis. The results of this study demonstrate that dry electrodes based on flexible CNT/PDMS composites and corrugated structures can outperform wet electrodes. The introduction of such electrodes is expected to enable the accurate analysis and monitoring of EEG signals in various scenarios, including clinical trials.

Polymers mixed with conductive fillers hold significant potential for use in stretchable and wearable sensor devices. Enhancing the piezoresistive effect and mechanical stability is critical for these devices. To explore the changes in the electrical resistance under high strains, typically unachievable in single-layer composites, bi-layer structures were fabricated from carbon nanotubes (CNTs) and EcoFlex composites to see unobservable strain regions. Spherical types of non-conductive fillers composed of polystyrene and conductive filler, coated with Ni and Au on non-conductive fillers, were used as secondary fillers to improve the piezoresistive sensitivity of composites, and their respective impact on the conductive network was compared. The electrical and mechanical properties were examined in the static state to understand the impact of these secondary fillers. The changes in the electrical resistance under 100% and 300% tensile strain, and their dependence on the inherent electrical properties of the secondary fillers, were also investigated. Single-layer CNT composites proved incapable of withstanding 300% strain, whereas the bi-layer structures proved resilient. By implementing cyclic stretching tests, contrary to non-conductive fillers, reduced piezoresistive influence of the conductive secondary filler under extreme strain conditions could be observed.