This paper studies the temperature dependence of the electrical resistivity of low-cost commercial graphene-based strips, made from a mixture of epoxy and graphene nanoplatelets. An equivalent homogenous resistivity model is derived from the joint use of experimental data and simulation results obtained by means of a full three-dimensional (3D) numerical electrothermal model. Three different types of macroscopic strips (with surface dimensions of cm²) are analyzed, differing in their percentage of graphene nanoplatelets. The experimental results show a linear trend of resistivity in a wide temperature range (−60°C to +60°C), and a negative temperature coefficient . The derived analytical model of temperature-dependent resistivity follows the simple law commonly adopted for conventional conducting materials, such us copper. The model is then validated by using the graphene strips as heating elements by exploiting the Joule effect. These results suggest that such materials can be used as thermistors in sensing or heating applications.

This article proposes an approach for smart monitoring of the life cycle of innovative graphene-based filters for water remediation in the presence of pollutants. The measurement technique is based on suitable figures of merit that analyze the time variation of the electrical impedance frequency spectrum. The proposed study considers the remediation of two toxic industrial pollutants, such as the acetonitrile and the 2,4-dichlorophenol. The contribution of this article is twofold. The first is the demonstration of a reliable monitoring setup that is able, for the selected use cases, to correlate in real time the behavior of the electrical impedance of the filter to its status, defined as “absence of pollutants” and/or “saturation.” The second contribution is the proposal of suitable figures of merit, based on measurement of the impedance frequency spectrum, able to increase the measurement sensitivity and the reliability and to mitigate some sources of uncertainty typically associated with these kinds of setups and measurements. Results show that the proposed graphene-based filters combine very good filtering capability and high sensitivity of the electrical impedance to the considered pollutants. These results suggest further investigations with other pollutants and the potential use of this technique for the predictive maintenance of the water filters in industrial applications, by endowing the graphene filters of smart sensing devices.

This paper investigates the possibility of realizing ice sensors based on the electrical response of thin strips made from pressed graphene nano-platelets. The novelty of this work resides in the use of the same graphene strips that can act as heating elements via the Joule effect, thus opening the route for a combined device able to both detect and remove ice. A planar capacitive sensor is designed and fabricated, in which the graphene strip acts as one of the armatures. The sensing principle is based on the high sensitivity of the planar capacitor to the change in electrical permittivity in the presence of ice, as shown in the experimental case study discussed here, can also be interpreted by means of a simple circuit and electromagnetic model. The properties of the sensor are analyzed, and the frequency range for its use as an ice detector has been established.

This paper provides a study of some relevant electro-thermal properties of commercial films made by pressed graphene nano-platelets (GNPs), in view of their use as heating elements in innovative de-icing systems for aerospace applications. The equivalent electrical resistivity and thermal emissivity were studied, by means of models and experimental characterization. Macroscopic strips with a length on the order of tens of centimeters were analyzed, either made by pure GNPs or by composite mixtures of GNPs and a small percentage of polymeric binders. Analytical models are derived and experimentally validated. The thermal response of these graphene films when acting as a heating element is studied and discussed.

This paper proposes a new technique to characterize the thermal conductivity and diffusivity of thin strips made by graphene nanoplatelets (GNP). The evaluation of these parameters is essential for a reliable design of thermal and electrothermal applications of graphene and is usually performed by means of assessed but expensive techniques such as those based on Raman effects and laser flash. The technique proposed here is simpler and less demanding in terms of equipment, and combines the results of an experimental characterization of the strip heated by the Joule effect obtained with infrared camera, with those provided by an electro-thermal model. Specifically, the evaluation of the thermal conductivity and diffusivity is the result of the analysis of the transient behavior of the measured and simulated solutions. The methodology is here successfully validated by applying it to commercial graphene strips and benchmarking against the thermal parameters provided by the manufacturers. Then, a complete characterization is provided for commercial strips based on different formulations of GNP and binders such as polyurethane, epoxy resin, and boron nitride. For these materials, the values of thermal conductivity and diffusivity are found in the ranges (50–450) W m⁻¹ K⁻¹ and (0.5–3.5) × 10⁻⁴ m² s⁻¹, respectively.

This paper investigates the feasibility of a multi-purpose use of thin films of industrial-grade graphene, adopted initially to realize advanced coatings for thermal management or electromagnetic shielding. Indeed, it is demonstrated that such coatings can be conveniently used as distributed temperature sensors based on the sensitivity of their electrical resistance to temperature. The study is carried out by characterizing three nanomaterials differing in the percentage of graphene nanoplatelets in the temperature range from −40 °C to +60 °C. The paper demonstrates the presence of a reproducible and linear negative temperature coefficient behavior, with a temperature coefficient of the resistance of the order of $-1.5·{10}^{-3}$${°\mathrm{C}}^{-1}$. A linear sensor model is then developed and validated through an uncertainty-based approach, yielding a temperature prediction uncertainty of approximately ±2 °C. Finally, the robustness of the sensor concerning moderate environmental variations is verified, as the errors introduced by relative humidity values in the range from 40% to 60% are included in the model’s uncertainty bounds. These results suggest the realistic possibility of adding temperature-sensing capabilities to these graphene coatings with minimal increase in complexity and cost.