Harvesting wind energy from the ambient environment is a feasible method for powering wireless sensors and wireless transmission equipment. Triboelectric nanogenerators (TENGs) have proven to be a stable and promising technology for harvesting ambient wind energy. This study explores a new method for the performance enhancement and practical application of TENGs. An array of flag-type triboelectric nanogenerators (F-TENGs) for harvesting wind energy is proposed. An F-TENG consists of one piece of polytetrafluoroethylene (PTFE) membrane, which has two carbon-coated polyethylene terephthalate (PET) membranes on either side with their edges sealed. The PTFE was pre-ground to increase the initial charge on the surface and to enhance the effective contact area by improving the surface roughness, thus achieving a significant improvement in the output performance. The vertical and horizontal arrays of F-TENGs significantly improved the power output performance. The optimal power output performance was achieved when the vertical parallel distance was approximately 4D/15 (see the main text for the meaning of D), and the horizontal parallel distance was approximately 2D. We found that the peak output voltage and current of a single flag-type TENG of constant size were increased by 255% and 344%, respectively, reaching values of 64 V and 8 μA, respectively.

Vibration measurement and analysis play an important role in diagnosing mechanical faults, but existing vibration sensors are limited by issues such as dependence on external power sources and high costs. To overcome these challenges, the use of triboelectric nanogenerator (TENG)−based vibration sensors has recently attracted attention. These vibration sensors measure a small range of vibration frequencies and are not suitable for measuring high-frequency vibrations. Herein, a self-powered vibration sensor based on an elastic steel triboelectric nanogenerator (ES−TENG) is proposed. By optimizing the elastic steel sheet structure and combining time-frequency transformation and filtering processing methods, the measurement of medium- and high-frequency vibrations is achieved. These results demonstrate that the ES−TENG can perform vibration measurements in the range of 2–10,000 Hz, with a small average error (~0.42%) between the measured frequency and external vibration frequency values. Therefore, the ES−TENG can be used as a self-powered, highly-accurate vibration sensor for intelligent machinery monitoring.

With the advantages of superior wear resistance, mechanical durability, and stability, the liquid–solid triboelectric nanogenerator (LS-TENG) has been attracting much attention in the field of energy harvesting and self-powered sensors. However, most of the studies on LS-TENG focused on device innovations, changes in solid materials, and the effect of solid properties on output performance, and there is a lack of studies on liquids, especially at the molecular level. A U-tube LS-TENG was assembled to conduct experiments, whereby the effects of molecular structures, including molecular composition, carbon chain length, functional groups and material properties on the output performance were investigated. The deuterium replacing hydrogen and the atomic compositions could not achieve the enhancement of the output performance. Whether the chemical functional groups improve the output performance of LS-TENG depends on the mating solid material. Hydroxyl and cyanogenic groups can improve the output performance for the FEP case, while amide and cyanogenic groups can improve the output performance for the PTFE case. The order of output performances for functional groups of four groups of liquids with both FEP and PTFE materials is also obtained. It was also found that the dielectric constant is not positively correlated with the output performance. The results of this study might provide a reference for the deeper study and application of LS-TENG.

Precise prediction of the power generation of photovoltaic (PV) stations on the island contributes to efficiently utilizing and developing abundant solar energy resources along the coast. In this work, a hybrid short-term prediction model (ICMIC-POA-CNN-BIGRU) was proposed to study the output of a fishing–solar complementary PV station with high humidity on the island. ICMIC chaotic mapping was used to optimize the initial position of the pelican optimization algorithm (POA) population, enhancing the global search ability. Then, ICMIC-POA performed hyperparameter debugging and L2-regularization coefficient optimization on CNN-BIGRU (convolutional neural network and bidirectional gated recurrent unit). The L2-regularization technique optimized the loss curve and over-fitting problem in the CNN-BIGRU training process. To compare the prediction effect with the other five models, three typical days (sunny, cloudy, and rainy) were selected to establish the model, and six evaluation indexes were used to evaluate the prediction performance. The results show that the model proposed in this work shows stronger robustness and generalization ability. K-fold cross-validation verified the prediction effects of three models established by different datasets for three consecutive days and five consecutive days. Compared with the CNN-BIGRU model, the RMSE values of the newly proposed model were reduced by 64.08%, 46.14%, 57.59%, 60.61%, and 34.04%, respectively, in sunny, cloudy, rainy, continuous prediction 3 days, and 5 days. The average value of the determination coefficient $R^{2 }$of the 20 experiments was 0.98372 on sunny days, 0.97589 on cloudy days, and 0.98735 on rainy days.

High heat flux brings about severe thermal problems for light-emitting diode (LED) automotive headlamps in narrow heat removal spaces, which will degrade their performance and lifespan. This study proposes an easily fabricated and feasible 1.3 mm thick 2D T-shaped in-plane ultra-thin vapor chamber (UTVC) for cooling the high heat flux of LED automotive headlamps. The effects of heating modes, unequal input heat load, and orientations on the thermal performance of the T-shaped UTVC are investigated. The results show that double-sided heating can improve the temperature uniformity of the T-shaped UTVC and reduce the thermal resistance compared to the single-sided heating. The lowest thermal resistances under single-sided and double-sided heating are 1.127 K/W at 12 W and 0.898 K/W at 16 W, respectively. When the total power is identical, the proposed 2D T-shaped UTVC can work effectively at unequal input power. The orientations have a significant impact on the thermal performance of the 2D T-shaped UTVC, and the thermal performance under different orientations changes with anti-gravity state < horizontal state < gravity-assisted state. The proposed T-shaped UTVC can work effectively under diverse operating ranges.

Real-time monitoring of marine ecosystems is crucial for global climate change research. In extreme marine environments such as the westerly regions in the Arctic and Antarctic, monitoring buoys and platforms often suffer from severe challenges, including insufficient energy supply, limited battery life, and difficult maintenance. Triboelectric nanogenerators (TENGs) offer a promising strategy for self-powered marine sensing. However, conventional tubular liquid–solid triboelectric nanogenerators (LS-TENGs) suffer from low efficiency of interfacial charge transfer due to limited contact area and excessive internal resistance, which restricts their output. In this study, a multi-tube nested liquid–solid triboelectric nanogenerator (MLS-TENG) is proposed, and the suitable filling ratio is determined through comparative experiments on structural parameters. This design significantly increases the effective contact area, reduces internal resistance, and improves synergistic charge transfer at multiple interfaces. Experimental results demonstrate that the MLS-TENG exhibits substantially improved electrical output compared with the corresponding single-tube structures. When integrated with a power management module, the capacitor charging efficiency is improved by approximately 120 times. In real sea trials, an array composed of MLS-TENG units successfully drives a self-powered sensing system, achieving stable 4G transmission of environmental parameters. This work provides a scalable structural optimization strategy for constructing high-performance blue energy-harvesting self-powered nodes for the marine Internet of Things.