As the proportion of Renewable Energy (RE) in the power system continues to increase and the number of Electric Vehicles (EVs) also grows year by year, the coordinated optimization of the two has become the key to enhancing the flexibility and stability of the power grid.Vehicle-to-Grid (V2G) technology, by enabling bidirectional energy exchange between electric vehicles and the power grid, provides an effective regulatory means to address the intermittency and volatility of renewable energy generation and is reshaping the operation mode of the power system.This article introduces the basic principles of V2G technology, the definition and types of RE, analyzes the existing collaborative mechanisms from three aspects: technology, market, policy and standard support, elaborates on the benefits that can be generated through the collaboration of the two, and discusses the challenges currently faced by the collaboration of V2G and RE in terms of user acceptance and battery life. Finally, the prospects for technological reform were made and the future research directions were pointed out.

Photoacoustic (PA) imaging relies on molecular systems with strong light absorption and efficient photothermal conversion. In this study, we performed DFT and TD-DFT calculations to investigate how electron-donating and electron-withdrawing substituents influence the photophysical properties of HS-CyBz-based probes. While these substituents modulate the excitation energies of both the thiol-containing reactant and the deprotected product, our results indicate that such a change alone does not significantly enhance the PA signal. These findings suggest that substituent modification is not an effective strategy for optimizing photoacoustic response. Instead, maximizing the difference in π-conjugation between the reactant and product is a more promising design approach for developing efficient PA probes.

With rapid urbanization, many low-rise residential buildings and certain indoor spaces suffer from inadequate natural lighting, relying heavily on artificial illumination. This dependence leads to increased energy consumption and potential exposure to harmful ultraviolet radiation. Existing indoor lighting systems typically use fixed light sources with limited adjustment capabilities, resulting in inefficient use of natural light and lacking ultraviolet filtration, which poses both energy and health challenges. To address these issues, this study proposes the "Medusozoa" intelligent solar energy utilization system, which achieves indoor natural lighting through efficient light collection, intelligent sunlight tracking, ultraviolet filtration, and optical fiber conduction technologies. The system employs a light sensor, an Arduino microcontroller, and a servo motor to track the sun's angle in real time, maximizing sunlight collection. It filters out harmful ultraviolet light and efficiently channels the filtered light indoors through optical fibers, significantly enhancing energy efficiency while ensuring health and safety.

Gallium nitride (GaN) wide bandgap devices generally have a low dielectric constant, high electron mobility, and a large bandgap. GaN is a common III-V material that has been widely used in the fabrication of electronic and optical devices such as light-emitting diodes (LEDs), lasers, and HEMTs. GaN photodetectors(PDs) are also widely used in the ultraviolet region for environmental monitoring, ultraviolet (UV) curing, etc. This article emphasizes the optoelectronic properties and semiconductor applications of GaN. GaN optoelectronic properties can be divided into three categories. The first one is band structure, which includes direct bandgap and wide bandgap (about 3.4 eV); the second one is optical properties, such as high luminous efficiency (for short wavelength emission) and absorption coefficient; the third one is electrical properties, mainly involving high breakdown field and high electron mobility (for high power devices). In addition, we discuss the application of GaN in semiconductor lasers by three different approaches. The first category is GaN-based laser structures; the second category is the application of GaN in semiconductor lasers, including blue/ultraviolet lasers and high-power lasers. Finally, we discuss challenges and advantages. Short wavelength, high efficiency, and good stability are mentioned as advantages in this section; material defects, cost, and thermal management are mentioned as disadvantages.

With the rapid development of renewable energy such as solar and wind power, the matching of supply and demand in the power system faces greater challenges. Electric vehicles (EVs) provide distributed energy storage services such as peak and valley regulation and frequency regulation to the power grid through a two-way vehicle-to-grid (V2G) system, which improves the flexibility and stability of the power grid. This paper proposes a unified framework based on artificial intelligence (AI) that integrates load forecasting, battery health-aware reinforcement learning scheduling, dynamic pricing, and multi-agent collaborative control, aiming to achieve efficient V2G operation in large-scale smart grids. By reviewing relevant literature, this paper analyzes the potential of the framework in improving grid stability, reducing operating costs, promoting the use of renewable energy, and extending battery life, and explores key challenges such as battery degradation, network security, system interoperability, and regulatory complexity. The study points out that the current model is mainly based on theory and simulation, lacking the support of large-scale empirical data. In the future, it is necessary to combine actual operation data and pilot projects to improve battery aging modeling and user behavior differentiation analysis to promote the practical application and optimization of the framework.

For efficient utilization of solar spectrum energy within 300-2500 nm, we propose a broadband solar absorber based on a metasurface with square-hollow configuration. The trilayer design employs "metal substrate/SiO2dielectric layer/hollow metal structure". Using COMSOL simulations, we investigate the regulatory mechanisms of material and geometric parameters on absorption performance. When zirconium (Zr) serves as the functional metal layer, the average absorption achieves 85% across 300-2500 nm, with peak efficiency approaching 100% at 1500 nm in the near-infrared regime. A COMSOL App is co-developed to democratize access, enabling cross-disciplinary intuitive control of geometric parameters. This explicitly validates Zr's broadband superiority from low-loss plasmonic resonance. The design accommodates fabrication processes including electron-beam lithography, providing an innovative pathway for solar power generation and photothermal conversion applications.

Power Electronic Transformers (PETs), integrating voltage conversion, electrical isolation, and power quality regulation, have been widely applied in smart grids, renewable energy systems, and rail transit. The emergence of wide-bandgap semiconductors, exemplified by SiC and GaN, together with advances in digital control methods, has accelerated progress in this field. PETs have gradually begun to replace traditional transformers, playing a significant role in flexible AC–DC hybrid grids. This paper systematically reviews the control strategies of PETs from three perspectives: modulation techniques, voltage and power balancing control strategies, and port control technologies. Finally, the paper summarizes the current technical challenges faced by PETs and discusses future development trends.

The high precision and reliability of satellite control systems heavily depend on fluid mechanics-related technologies. In microgravity environments, fluid behavior significantly differs from terrestrial conditions, posing challenges for critical operations such as propellant management, thermal control, and attitude stabilization. This paper systematically reviews recent advances in fluid mechanics applications for satellite control systems, focusing on three key aspects: (1) microgravity fluid dynamics in propulsion systems, (2) fluid mechanics in thermal control systems, and (3) fluid-based attitude control methods. Traditional Navier-Stokes equations require modifications incorporating dimensionless parameters (e.g., Bond number, capillary number), while numerical simulations and ground-based experiments serve as primary research tools. The analysis identifies the key hurdles in applying fluid mechanics to satellite control: ensuring long-term orbital fluid stability, untangling multi-physics couplings, and overcoming engineering bottlenecks in next-generation fluid technologies. Future research directions encompass intelligent fluid control, cost-effective solutions for commercial space applications, and extreme-environment adaptability designs for deep-space exploration.

Amid global efforts toward energy conservation and carbon reduction in maritime transport, this study proposes an interdisciplinary optimization framework integrating predictive analytics with advanced energy systems to address challenges in vessel decarbonization. A Transformer-LSTM hybrid model is developed to forecast emission patterns using historical operational data, enabling dynamic navigation strategy adjustments. The complementary quadruple-heat supply system synergizes waste heat recovery, energy efficiency optimization, and carbon capture technologies through an integrated control architecture. Case studies demonstrate significant improvements in both Energy Efficiency Existing Ship Index (EEXI) and Carbon Intensity Indicator (CII), achieving 18.7% enhancement in energy utilization efficiency and 22.4% reduction in operational carbon intensity compared to conventional systems. The proposed solution offers a cost-effective pathway for retrofitting legacy vessels, particularly in optimizing power distribution and thermal management under varying operational conditions. Quantitative analysis reveals the system's potential to reduce annual greenhouse gas emissions by 34-41% per vessel, substantiating its contribution toward achieving IMO's 2050 decarbonization targets. This research establishes a methodological framework for intelligent energy-carbon synergy control in maritime applications, providing both theoretical advancements and practical implementation strategies for the shipping industry's low-carbon transition.

Nanofluids have the potential to enhance heat transfer efficiency and increase safety margins in nuclear reactor cooling systems due to their superior thermophysical properties, such as significantly improving the thermal conductivity of the base liquid and enhancing convective heat transfer and critical heat flux. However, the deposition of nanoparticles within the system causes complex clogging problems, resulting in reduced flow channel cross-sectional area, increased pressure drop, deteriorated heat transfer and equipment wear. The blockage is caused by the combined effects of nanoparticle characteristics, fluid dynamics conditions and environmental or material factors (e.g., temperature, pressure, wall roughness). The clogging behavior of nanofluids in special conditions (such as strong corrosiveness and radiation fields) for advanced reactors (lead-cooled fast reactors, sodium-cooled fast reactors, molten salt reactors, and supercritical water-cooled reactors) has not been fully elucidated. Future work should focus on surface-modified particles, multi-scale simulations/machine learning for deposition prediction, and long-term behavior in extreme conditions. Controlling blockages is critical for scaling nanofluids in nuclear energy.