Integrated manufacturing of REciclable multi-material COmposites for the TRANSport sector
Insights into the Electrical Characterization of Graphene-like Materials from Carbon Black
A new class of graphene-related materials (GRMs) obtained as water suspensions through a two-step oxidation/reduction of a nanostructured carbon black, namely graphene-like (GL) materials, has recently emerged. GL materials undergo self-assembly in thin amorphous films after drying upon drop-casting deposition on different surfaces. The GL films, with thicknesses of less than a micron, were composed of clusters of nanoparticles each around 40 nm in size. The exploitation of the GL films for different options (e.g., bioelectronic, sensoristic, functional filler in composite) requires a deep characterization of the material in terms of their electric transport properties and their possible interaction with the surface on which they are deposited. In this work, a careful electrical characterization of GL films was performed at room temperature and the results were compared with those achieved on films of benchmark graphenic materials, namely graphene oxide (GO) materials, obtained by the exfoliation of graphite oxide, which differ both in morphology and in oxidation degree. The results indicate a non-linear current–voltage relationship for all the investigated films. The extrapolated dielectric constant (ε) values of the investigated GRMs (GL and GO materials) agree with the experimental and theoretically predicted values reported in the literature (ε~2–15). Because similar conductance values were obtained for the GL materials deposited on glass and silicon oxide substrates, no significant interactions of GL materials with the two different substrates were highlighted. These results are the starting point for boosting a feasible use of GL materials in a wide spectrum of applications, ranging from electronics to optics, sensors, membranes, functional coatings, and biodevices.
» Author: Raffaella Ferraiuolo
» Reference: doi: 10.3390/coatings12111788
» Publication Date: 21/11/2022
This project has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement Nº 768737
