The deficiencies of conventional battery-based sensors such as limited lifetime, risk of environmental pollution, and low device maintainability [6,7] have been gradually exposed to be insufficient to settle down the explosive increase of these decentralized sensors. Thus, self-powered technology that harvests environmental energy as sustainable power supply has become an attractive and sustainable solution to the restraints of conventional power supply. [8][9][10][11] Among all types of ambient energy, wind energy is regarded as the most ubiquitous and sustainable energy source in our daily life with huge quantities. [12][13][14][15] Traditionally, the wind energy generally refers to medium and strong winds with wind speeds over 4.0 m s −1 , which is an efficient working range for most of wind harvesting technologies. [16][17][18][19] However, the global average wind speed near the surface with an observation altitude of 10 m in height is reported to be 3.28 m s −1 , [10,18] which implies the inadequate utilization of the most prevalent wind energy resources in low wind speed by current technology. In decades, wind power generations with electromagnetic generators (EMGs) have been widely used in the wind farm, [20,21] but still difficult to apply in distributed miniature power supply for their bulky and heavy inherent A triboelectric nanogenerator (TENG) based self-powered system for wind energy harvesting introduces a desirable solution to alleviate the expanding energy supply concerns in the development of the internet of things. In this work, an auto-switching self-powered system based on a dual-rotation shaft TENG (D-TENG) is reported to effectively harvest wind energy over a broad-band wind speed (2.2-16 m s −1 ). The D-TENG is designed in a concentric dual-rotation shaft structure, in which two independent TENGs with different shapes, sizes, and arm lengths of wind cups are rationally coupled. The integration of the two TENGs with varied structural parameters achieves mutual compensation of their own merits, enabling the whole system to have preferable aerodynamics and high energy conversion efficiency over a broad range of wind speeds. Moreover, an electromagnetic generator (EMG) with the same energy collection module is also fabricated for a comparison with TENG in the start-up properties and average output power. Furthermore, a packaged self-powered system is demonstrated for simulated wind energy harvesting, while the charging characteristics are also discovered. The proposed TENG renders a more efficient technique for energy harvesting and greatly expands its potential in the large-scale wind energy harvesting that can be attributed to the multi-stage strategy.

Natural wind energy harvesting enables a far‐reaching and sustainable solution to supply pervasive sensors in the Internet of Things (IoT). Electromagnetic generators (EMGs) struggle to harvest energy from breezes, which causes regrettable energy wastage. Herein, a triboelectric‐electromagnetic hybridized nanogenerator (TEHG) is designed with a dual‐rotor structure to consolidate harvesting band for high efficiency of triboelectric nanogenerators (TENGs) in breeze and the EMG in high wind speeds. The TEHG performs an efficient energy collection (41.05 W m−3) and a smooth output in the wind speed of 2−16 m s−1, attributed to the environmental self‐adaptive cooperation between TENGs and EMGs. The TENG output power contribution is more than 70% at low wind speeds (<5 m s−1). Moreover, a dual‐channel power management topology (DcPMT) is established to co‐manage outputs of two modules in TEHG. By virtue of the DcPMT hierarchically combining the isolated storage with undervoltagelockout strategy, the TEHG steadily supplies a standardized 3.3 V voltage for commercial electronics. Furthermore, a TEHG‐based self‐powered system is demonstrated for driving sensors to monitor meteorological information. The TEHG with DcPMT is advantageous in broad‐band and high‐efficiency of wind energy harvesting, thus exhibiting a great potential for elevating the environmental self‐adaptability and stability margin of the IoT.

An agglomeration phenomenon characterized by nanoparticle dispersion is a decisive factor that reflects the degree of the maintained overall performance of nanofluids and other nanocomposites. However, the quantitative characterization and non-destructive measurement for nanofluid dispersion (NFD) still remain challenged. Herein, an in situ NFD measurement system based on a variable frequency liquid-solid triboelectric nanogenerator (VFLS-TENG) is developed. This work utilizes VFLS-TENG as a passive probe and proposes an equivalent capacitance circuit model for detecting NFD based on the electric double layer model at liquid-solid interfaces. In the circuit model, a quantitative calculation process for both particle size and spacing is introduced through parameter identification using the Quantum Genetic and Levenberg-Marquardt hybrid algorithm, and parameter separation using the Runge-Kutta algorithm. The results demonstrates a good agreement with the traditional methods, among which the measured particle size is more accurate than the hydrodynamic diameter of dynamic light scattering by 28.6% with a high sensitivity of 1667 nm nF −1 . The proposed method is capable of measuring the effective charge on the nanoparticle surface in situ, and simultaneously obtaining the particle size and spacing for the online monitoring NFD, thus further facilitating the controllable preparation during the nano-composites modification, and quantitative optimization of nanofluid design performance.