Intelligent triboelectric sliding bearing for gas leak self-sensing and mechanical fault self-diagnosis in green ammonia production

To address carbon neutrality and peak carbon emissions, harvesting mechanical energy from bearings and converting it into electrical energy to drive ammonia leakage alarm, as well as bearings’ mechanical fault self-diagnosis, is challenging yet highly demanded in the green ammonia production industry. Herein, we demonstrated an Intelligent Triboelectric Sliding Bearing (ITSB) system, featuring a free-standing rotary barrel-shaped triboelectric nanogenerator (TENG), a gallium oxide (Ga₂O₃)/MXene nanocomposite-based NH₃ gas sensor and a self-driven data transmission unit. In addition to retaining the traditional load-bearing function, the free-standing rotary barrel-shaped TENG converted the friction from rotational motion into electrical energy, providing continuous power for sensing and data transmission. Low-cost Ga₂O₃/MXene composite was fabricated as a gas-sensitive film for NH₃ using a combined hydrothermal synthesis and physical composite method. The composite film-based interdigitated electrode demonstrated a highly sensitive (65.7 % @2 ppm) and fast response (5 s@2 ppm) to NH₃ gas with surface synergy effect performance confirmed through density functional theory calculations (DFT). Additionally, the self-driven data transmission unit were implemented to autonomously regulate and store the free-standing rotary barrel-shaped TENG output for sensing and mechanical operation monitoring. A neural network algorithm was developed to predict mechanical failures of bearings. By integrating on-site data, the accuracy reached 99 %. This integrated system paves a practical solution for gas sensing and mechanical fault diagnosis of bearings in green ammonia production for its sustainable and safe development.