Recently, graphene and other graphene-based materials have become an essential part of composite science and technology. Their unique properties are not only restricted to graphene but also shared with derivative compounds like graphene oxide, reduced graphene oxide, functionalized graphene, and so forth. One of the most structurally important materials, graphene oxide (GO), is prepared by the oxidation of graphite. Though removal of the oxide groups can create vacancies and structural defects, reduced graphene oxide (rGO) is used in composites as effective filler similar to GO. Authors developed a new polyurethane nanocomposite using a derivative of grapheme, thermally reduced graphene oxide (rGO), to modify the matrix of polyurethane elastomers, by rGO.

Utilizing the electrical properties of polymer nanocomposites is an important strategy to develop high performance solvent sensors. Here we report the synergistic effect of multi walled carbon nanotubes (MWCNTs) and reduced graphene oxide (RGO) in regulating the sensitivity of the naturally occurring elastomer, natural rubber (NR). Composites were fabricated by dispersing CNTs alone and together with exfoliated RGO sheets (thermally reduced at temperatures of 200 and 600 °C ) in NR by a solution blending method. RGO exfoliation and the uniform distribution of fillers in the composites were studied by atomic force microscopy, Fourier transformation infrared spectroscopy, X-ray diffraction, transmission electron microscopy and Raman spectroscopy. The solvent sensitivity of the composite samples was noted from the sudden variation in electrical conductivity which was due to the breakdown of the filler networks during swelling in different solvents. It was found that the synergy between CNTs and RGO exfoliated at 200 °C imparts maximum sensitivity to NR in recognizing the usually used aromatic laboratory solvents. Mechanical and dynamic mechanical studies reveal efficient filler reinforcement, depending strongly on the nature of filler–elastomer interactions and supports the sensing mechanism. Such interactions were quantitatively determined using the Maier and Göritz model from Payne effect experiments. It is concluded that the polarity induced by RGO addition reduces the interactions between CNTs and ultimately results in the solvent sensitivity.

We report the fabrication of graphene oxide (GO) based polyurethane (PU) nanocomposites by a simple method of mixing and their shape memory properties at different temperatures. Both the polymer and the filler were synthesized in the laboratory by simple and easy methods – PU by pre-polymer method and GO by improved graphene oxide synthesis method. High molecular level dispersion of GO platelets within the PU matrix and thus good mechanical properties were maintained by the improved PU/GO interfacial interaction. The structure of the polymer composites was investigated by scanning electron microscopy and X-ray diffraction studies revealed a highly dispersed morphology of graphene oxide sheets in PU. The improvement in shape memory obtained for the nanocomposites was then quantitatively analysed using the Payne effect. The crosslink density calculated using the Maier and Göritz model (Payne effect) was found to be dependent on the thermal transitions of the composites and it varied with the filler concentration. Accordingly a nice correlation was established between the temperature dependence of shape memory and the crosslink density. Composite behaviour was further analysed by the dynamic measurements such as rheology, stress relaxation and Mullins effect. To the best of our knowledge, the quantification of shape memory in terms of physical crosslinks and filler–polymer entanglements of the PU/GO nanocomposite system has not been addressed before and is introduced in this work.

Polyurethane/graphene nanocomposites were synthesized using commercial thermoplastic polyurethane (TPU, Apilon 52DE55), and two types of graphene derivatives: graphene nanoplatelets (GNP) and reduced graphene oxide (RGO). Fourier Transformation Infrared Spectroscopy Fourier Transformation Infrared Spectroscopy (FTIR) spectroscopy, TEM, and SEM microscopy and XRD techniques were used to chemically and structurally characterize GNP and RGO nanofillers. The properties of the new TPU nanocomposite materials were studied using thermal analysis techniques (Dynamical Mechanical Analysis (DMA), Differential Scanning Calorimetry (DSC), Thermogravimetric Analysis (TG)) to describe the influence of graphene nanofillers on polyurethane matrix. Our investigation describes the comparison of two types of graphene derivatives, commercial one (GNP) and synthesized (RGO) on thermoplastic polyurethanes. These nanofillers provides opportunities to achieve compatibility with the TPU matrix. The property enhancements are attributed commonly to high aspect ratio of graphene nanoplatelets and filler–polymer interactions at the interface. The obtained nanocomposites exhibit higher thermal and mechanical properties due to the good dispersion of both nanofillers into TPU matrix. It was found that the addition of 2 wt % of the nanofiller could lead to a significant reinforcement effect on the TPU matrix. Also, with high content of nanofiller (GNP and RGO), the Payne effect was observed.

In recent years, portable and wearable personal electronic devices have rapidly developed with increasing mass production and rising energy consumption, creating an energy crisis. Using batteries and supercapacitors with limited lifespans and environmental hazards drives the need to find new, environmentally friendly, and renewable sources. One idea is to harness the energy of human motion and convert it into electrical energy using energy harvesting devices—piezoelectric nanogenerators (PENGs), triboelectric nanogenerators (TENGs) and hybrids. They are characterized by a wide variety of features, such as lightness, flexibility, low cost, richness of materials, and many more. These devices offer the opportunity to use new technologies such as IoT, AI or HMI and create smart self-powered sensors, actuators, and self-powered implantable/wearable devices. This review focuses on recent examples of PENGs, TENGs and hybrid devices for wearable and implantable self-powered systems. The basic mechanisms of operation, micro/nano-scale material selection and manufacturing processes of selected examples are discussed. Current challenges and the outlook for the future of the nanogenerators are also discussed.