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    Three-dimensional graphene foam based triboelectric nanogenerators for energy systems and autonomous sensors

    Year: 2023

    Journal: Nano Energy, Volume 112, 2023-07-01, page 108475

    Authors: Keel, Emma; Ejaz, Ammara; Mckinlay, Michael; Garcia, Manuel Pelayo; Caffio, Marco; Gibson, Des; García Núñez, Carlos

    Keywords: Triboelectric nanogenerator; 3D graphene; Energy harvesting; Self-powered sensors

    In this work we investigate the potential of three-dimensional graphene (3DG) foam as an active layer in triboelectric nanogenerators (TENGs) and as an energy harvesting power source for autonomous sensors. A series of comprehensive measurements have been carried out to test the output characteristics of 3DG-TENG under cyclic mechanical stimulus, capable of operating TENG in contact-separation mode at different frequencies, gap distances between electrodes, and applied pressures. The triboelectric response of 3DG-TENG (with an effective surface of 16 cm2) showed maximum open-circuit voltage (Voc) and short-circuit current (Isc) of 400 V and 105.7 μA respectively when stimulated at 3 Hz (contact-separation frequency) and 70 mm (optimum gap distance). Under the same conditions, a maximum output power (Pout) of around 10.37 W/m2 is produced using an external load resistance of 40 MΩ; this is an order of magnitude lower resistance than that needed with other graphene based TENG variants. 3DG-TENG exhibited great stability in the output characteristics with 15,000 cyclic mechanical stimuli and a retention percentage in Pout above 95%. This is a significant improvement with respect to other carbon based TENG`s, which show enhanced deterioration of TENG performance due to material transfer between electrodes and plastic deformation of triboelectric materials. Simulations of TENG Voc using distance dependent model determined high triboelectric charge densities in the range of mC/m2. Here, we also demonstrate the potential of 3DG-TENG as an energy supply for energy storage devices, and as an active layer in an autonomous pressure sensing platform for anonymous room occupancy monitoring in smart buildings.
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