Porosity Modulated High-Performance Piezoelectric Nanogenerator Based on Organic/Inorganic Nanomaterials for...

In the modern era, structural health monitoring (SHM) is critically important and indispensable in the aerospace industry as an effective measure to enhance the safety and consistency of aircraft structures by deploying a reliable sensor network. The deployment of built-in sensor networks enables uninterrupted structural integrity monitoring of an aircraft, providing crucial information on operation condition, deformation, and potential damage to the structure. Sustainable and durable piezoelectric nanogenerators (PENGs) with good flexibility, high performance, and superior reliability are promising candidates for powering wireless sensor networks, particularly for aerospace SHM applications. This research demonstrates a self-powered wireless sensing system based on a porous polyvinylidene fluoride (PVDF)-based PENG, which is prominently anticipated for developing auto-operated sensor networks. Our reported porous PVDF film is made from a flexible piezoelectric polymer (PVDF) and inorganic zinc oxide (ZnO) nanoparticles. The fabricated porous PVDF-based PENG demonstrates ∼11 times and ∼8 times enhancement of output current and voltage, respectively, compared to a pure PVDF-based PENG. The porous PVDF-based PENG can produce a peak-to-peak short-circuit current of 22 μA, a peak-to-peak open-circuit voltage of 84.5 V, a peak output power of 0.46 mW $$, and a peak output power density of 41.02 μW/cm² (P/A). By harnessing energy from minute vibrations, the fabricated porous PVDF-based PENG device (area of A = 11.33 cm²) can generate sufficient electrical energy to power up a customized wireless sensing and communication unit and transfer sensor data every ∼4 min. The PENG can generate sufficient electrical energy from an automobile car vibration, which reflects the scenario of potential real-life SHM systems. We anticipate that this high-performance porous PVDF-based PENG can act as a reliable power source for the sensor networks in aircraft, which minimizes potential safety risks.