The anhydride-cured epoxy resin can be made into structural parts such as wind turbine blades and girders by pultrusion process. After crosslinking, it is difficult to degrade and recycle, which is one of the difficulties in the treatment of wind turbine blades. Methyl tetrahydro phthalic anhydride is a kind of anhydride curing agent. The effects of different liquid organic amines, different catalysts and different process conditions on the degradation of epoxy resin block cured by this anhydride were studied, and the best combination of degradation solution and degradation catalyst and degradation process conditions were determined, which realized the rapid degradation of anhydride cured epoxy system. At the same time, the degraded products were extracted and separated, and detected by infrared ray (IR) and nuclear magnetic resonance (NMR), and the main components of the recovered products were determined. Moreover, the degradation mechanism of the anhydride-cured epoxy resin by liquid organic amine was deduced, which provided a new idea and beneficial exploration for chemical recovery and reuse of the anhydride-cured epoxy resin.

With the expansion of glass fiber-reinforced plastic (FRP) products market, its output increases year by year. At the same time, the amount of its waste also increases dramatically. The number of waste FRP will increase explosively in the next few years. To develop a new way for recycling waste FRP, the broken waste fan blade powder is investigated. Firstly, the morphology and structure of the waste fan blade powder are tested. Secondly, the waste fan blade powder is modified by liquid coupling agent KH-550 and liquid paraffin, and then mixed with polyethylene (PE). Finally, the mechanical properties of the obtained material are analyzed. The experimental results show that, the longitudinal shrinkage rate of the modified composite reduced by 49.85% compared with that of the conventional formula, and the tensile strength, elongation at break and simply supported beam impact strength increased by 66.11%, 21.58% and 42.72%, respectively

Focusing on the structural safety of a three-column floating foundation for floating wind turbines, this study systematically assesses its stability, ultimate strength, and fatigue strength. A full-scale finite element model is established using the SESAM software suite. Intact and damaged stability analysis is conducted according to relevant codes. The result indicates that all parameters comply with regulatory requirements and demonstrate excellent anti-overturning capability. In the ultimate strength analysis, based on load conditions considering various wave directions, amplitudes, and periods, it is found that the maximum structural stress concentration occurs at the connections between the buoyancy tanks and columns. Nevertheless, the overall stress levels remain within the design resistance limits. Employing the hotspot stress approach, fatigue strength assessment of critical connection areas shows that the fatigue damage at all checkpoints is less than 1, satisfying the design life requirements. The floating foundation structure meets all applicable code standards for stability, ultimate strength, and fatigue strength. Therefore, the research provides a significant safety basis for the engineering application of floating wind turbines in deep-sea environments. It also offers valuable methodology and guidance for safety assessments of similar projects.

To optimize the process parameters for the preparation of regenerated products by mixing the powder of waste wind turbine blades with high-density polyethylene (HDPE) and remolding, the Six-sigma DoE method was used to design the experiments to study the effects of various process parameters such as barrel temperature in each zone, confluence core temperature, mold temperature, and main engine speed on the performance of regenerated products. The flexural strength and compressive strength were used as the evaluation indexes of the performance of regenerated products, and the optimum remolding process preparation parameters were obtained combined with the given matching value. The experimental results show that when the flexural strength of 44 MPa and the compressive strength of 31 MPa are selected as target matching values, the optimal process parameters obtained by maximizing the preferred parameters are: front zone barrel temperature of 189 ℃, middle zone barrel temperature of 179 ℃, rear zone barrel temperature of 168 ℃, confluence core temperature of 158 ℃, mold temperature of 156 ℃, and main engine speed of 4.0 r/min. Under this process condition, the flexural strength of the regenerated product is 43.15 MPa, and the compressive strength is 30.73 MPa.

Floating offshore wind turbines (FOWTs) are affected by various factors in the marine environment, which can significantly alter their motion states and thereby affect their power generation performance. The influences of ocean currents on motion response of the FOWTs under different wind and wave conditions are investigated, and their impacts on power output are also studied. A semi-submersible floating platform equipped with a 5 MW wind turbine is selected as the research object, and simulations are conducted using OpenFAST, FAST to AQWA (F2A), and AQWA software. The surge, heave, and pitch motion responses of the floating platform, as well as the power generation output, are calculated under three environmental conditions: steady wind with regular waves, steady wind with irregular waves, and turbulent wind with irregular waves. The motion responses and power generation output are then recalculated after the incorporation of ocean currents. The results indicate that ocean currents primarily have a significant impact on surge motion, with a maximum difference of up to 13%, while their effects on heave and pitch motions are relatively minor. In the calculation of power output under the three environmental conditions, ocean currents show no influence on the average or maximum power generation output of the wind turbine, with differences of less than 1% between cases. Additionally, under more complex conditions, the standard deviation of power generation output exhibits minimal variation, suggesting that ocean currents do not affect the fluctuation intensity of power output.

The resource-recycling of retired crystalline-silicon photovoltaic cells is of great significance for the recycling of materials and the green and healthy development of renewable energy. Currently, most recyclers of decommissioned photovoltaic modules mainly focus on the recycling of aluminium frames, while aluminium resources in crystalline-silicon solar cells have not been effectively recycled, leaving valuable silver within the cells. Therefore, a wet-recycling process for preparing silver powder was proposed, which involves leaching aluminum with liquid alkali, leaching silver with nitric acid, and liquid-phase reduction. By optimizing the experimental parameters, under the conditions of a sodium-hydroxide concentration of 1.0 mol/L, a temperature of 20 ℃, a liquid-to-solid ratio of 10:1 (mL/g), and a reaction time of 40 min, the leaching rate of aluminum from the retired crystalline-silicon photovoltaic cells reached 98.88%, and the leaching-loss rate of silicon was only 0.46%. Under the conditions of a nitric-acid concentration of 4.0 mol/L, a temperature of 70 ℃, a liquid-to-solid ratio of 5:1 (mL/g), and a reaction time of 60 min, the leaching rate of silver reached 98.00%. Using ascorbic acid as a reducing agent, silver powder with a purity of over 99.9% was successfully prepared under the conditions of a molar ratio of ascorbic acid to silver ions of 1.25:1.00, a temperature of 30 ℃, and a stirring speed of 250 r/min. This process achieves high recovery rates and product purity, offering a practical pathway for crystalline silicon solar cell wafers recycling.

The efficient valorization of CO₂ and N₂ from power plant flue gas represents a critical pathway toward advancing the low-carbon transition of energy systems. Electrochemical synthesis of urea by directly coupling CO₂ and N₂ in flue gas under ambient conditions offers dual benefits: converting greenhouse gases into high-value fertilizers while achieving carbon mitigation and resource recycling. This review systematically summarizes recent advancements in this field, highlighting optimized reaction pathways through novel catalyst designs such as heterojunction catalysts and conductive MOFs, which enhance the synergistic activation of N₂ and CO₂ and improve C-N coupling efficiency, achieving a record Faradaic efficiency of 48% for urea production. Future breakthroughs should focus on developing bioinspired catalytic materials, integrating photo-electrocatalytic systems, and innovating renewable-powered integrated processes for carbon capture-conversion-product separation. By analyzing technical principles, engineering challenges, and industrial linkages, this work underscores the pivotal role of electrocatalytic urea synthesis in coordinated carbon-nitrogen management for coal-fired power plants, providing a forward-looking strategic thinking for scaling up this transformative technology.

To address the intermittent and unstable power output issues in hydrogen production from renewable energy sources such as wind and solar power, it is crucial to achieve the optimal configuration of green power hydrogen production equipment. The discrete combinatorial optimization algorithms and multi-objective shuffled frog leaping algorithms are study introduced to conduct optimization research on the planning of parks with pure photovoltaic, pure wind power, and photovoltaic-wind power hybrid systems for renewable energy generation. Models of electrolyzer system efficiency, operating power, cost, and capacity are constructed. The results show that in a hybrid system with a photovoltaic capacity of 2.60 MW and a wind power capacity of 3.80 MW, the lowest hydrogen levelized cost is 17.83 yuan/kg, and the full-load operating hours of the electrolyzer are approximately 3 400 hours. After optimization by the multi-objective shuffled frog leaping algorithm, the optimal configuration is a photovoltaic capacity of 1.50 MW and a wind power capacity of 0.55 MW, with a maximum hydrogen production of 2 949.62 kg. The photovoltaic-wind power hybrid system can not only reduce the hydrogen levelized cost but also increase the full-load operating time, providing a theoretical reference for the scientific planning of hydrogen production from renewable energy in the future.

The Brayton cycle-based tower solar thermal power system features a flexible layout and operates at high receiver temperatures. However, fluctuations in solar irradiance can lead to thermal fatigue of receiver materials or excessive surface temperatures, necessitating effective strategies to mitigate temperature fluctuations. This study develops a manganese-based thermochemical thermal protection coating utilizing a reversible redox reaction. When solar radiation intensifies and the temperature exceeds 978 ℃, the coating undergoes a reduction endothermic reaction, reducing the heating rate. Conversely, when solar radiation decreases and the temperature drops below 878 ℃, an oxidation exothermic reaction occurs, slowing the cooling rate, thereby stabilizing receiver surface temperature fluctuations. Experimental results indicate that when the mass ratio of the coating material to the binder is 4:3, the adhesion strength reaches the highest national standard level, and the solar weighed average absorptivity achieves 94.93%. After undergoing 500 hours of thermal aging at 950 ℃, 100 cycles of thermal cycling, and 200 cycles of redox reaction tests, the coating’s weighed average absorptivity decreased by only 0.82, 0.98, and 2.61 percentage points, respectively, while maintaining the highest adhesion strength. Under a sudden change in concentrated solar radiation flux of ±9.7 kW/m², the heating and cooling rates in the first 100 seconds were reduced by 59.66% and 67.09%, respectively. Additionally, the time required for a 20 ℃ increase and decrease was extended by 182.50% and 438.60%, respectively. The manganese-based thermochemical coating demonstrates excellent aging resistance and effectively suppresses absorber temperature fluctuations, making it highly promising for applications in Brayton cycle-based tower solar thermal power systems.

To address the challenges of meteorological-power response inaccuracy, difficulty in capturing abrupt features, and data scarcity in photovoltaic power prediction under extreme weather conditions, a hybrid prediction framework is proposed based on fuzzy C-means (FCM), maximum information coefficient (MIC), time variational auto-encoders (TimeVAE), 1D convolutional neural network (1DCNN), and simple-Mamba (S-Mamba). Firstly, meteorological features are clustered using FCM to categorize weather into four types: sunny, cloudy, snowy, and rainy. Subsequently, MIC is employed to select the optimal subset of meteorological features. To mitigate the scarcity of extreme weather samples, TimeVAE is adopted for data generation, leveraging its decomposed reconstruction mechanism to synthesize realistic time-series data. Finally, a 1DCNN-S-Mamba combined model is utilized, where 1DCNN captures short-term abrupt features through local convolution, while bidirectional state-space modeling in S-Mamba enables long-range dependency analysis for prediction. Experimental results demonstrate that the proposed model enhances both timeliness and accuracy in PV power prediction under complex weather conditions. Compared to S-Mamba, it reduces the mean absolute error (MAE) and root mean square error (RMSE) by 3.65% and 5.10%, respectively, in snowy weather scenarios.