China, People’s Republic

Green hydrogen plays a pivotal role in decarbonizing our energy system and achieving the Net-Zero Emissions goal by 2050. Offshore wind farms (OWFs) dedicated to green hydrogen production are currently recognized as the most feasible solution for scaling up the production of cost-effective electrolytic hydrogen. However the cost associated with distribution and transmission systems constitute a significant portion of the total cost in the large-scale wind-hydrogen system. This study pioneers the simultaneous optimization of the inter-array cable routing of OWFs and the location and capacity of offshore hydrogen production platforms (OHPPs) aiming to minimize the total cost of distribution and transmission systems. Considering the characteristics of hydrogen production efficiency this paper constructs a novel mathematical model for OHPPs across diverse wind scenarios. Subsequently we formulate the joint planning problem as a relaxed mixed-integer second-order cone programming (MISOCP) model and employ the Benders decomposition algorithm for the solution introducing three valid inequalities to expedite convergence. Through validation on real-world large-scale OWFs we demonstrate the validity and rapid convergence of our approach. Moreover we identify hydrogen production efficiency as a major bottleneck cost factor for the joint planning problem it decreases by 1.01% of total cost for every 1% increase in hydrogen production efficiency.

Water electrolyzers play a crucial role in green hydrogen production. However their efficiency and scalability are often compromised by bubble dynamics across various scales from nanoscale to macroscale components. This review explores multi-scale modeling as a tool to visualize multi-phase flow and improve mass transport in water electrolyzers. At the nanoscale molecular dynamics (MD) simulations reveal how electrode surface features and wettability influence nanobubble nucleation and stability. Moving to the mesoscale models such as volume of fluid (VOF) and lattice Boltzmann method (LBM) shed light on bubble transport in porous transport layers (PTLs). These insights inform innovative designs including gradient porosity and hydrophilic-hydrophobic patterning aimed at minimizing gas saturation. At the macroscale VOF simulations elucidate two-phase flow regimes within channels showing how flow field geometry and wettability affect bubble discharging. Moreover artificial intelligence (AI)-driven surrogate models expedite the optimization process allowing for rapid exploration of structural parameters in channel-rib flow fields and porous flow field designs. By integrating these approaches we can bridge theoretical insights with experimental validation ultimately enhancing water electrolyzer performance reducing costs and advancing affordable highefficiency hydrogen production.

Hydrogen as a clean energy source has gradually become an important choice for the energy transformation in the world. Utilizing existing natural gas pipelines for hydrogen-blended transportation is one of the most economical and effective ways to achieve large-scale hydrogen transportation. However hydrogen can easily penetrate into the pipe material during the hydrogen-blended transportation process causing damage to the properties of the pipe. The heat-affected zone (HAZ) of the weld being the weakest part of the pipeline is highly sensitive to hydrogen embrittlement. The microstructure and properties of the grains in the heat-affected zone undergoes changes during the welding process. Therefore this paper divides the HAZ of X80 welded pipes into three sub-HAZ namely the coarse-grained HAZ fine-grained HAZ and intercritical HAZ to study the hydrogen behavior. The results show that the degree of hydrogen damage in each sub-HAZ varies significantly at different strain rates. The coarse-grained HAZ has the highest hydrogen embrittlement sensitivity at low strain rates while the intercritical HAZ experiences the greatest hydrogen damage at high strain rates. By combining the microstructural differences within each sub-HAZ the plastic damage mechanism of hydrogen in each sub-HAZ is analyzed with the aim of providing a scientific basis for the feasibility of using X80 welded pipes in hydrogen-blended transportation.

This study investigates the effects of secondary jet-guided combustion on the combustion and emissions of a hydrogen direct-injection engine through numerical simulations. The results show that secondary jet-guided combustion which involves injecting and igniting the hydrogen jet at the end of the compression stroke significantly shortens the delay period improves combustion stability and brings the combustion center closer to the top dead center (TDC) achieving a maximum indicative thermal efficiency (ITE) of 46.55% (λ = 2.4). However this strategy results in higher NOx emissions due to high-temperature combustion. In contrast single and double injections lead to worsened combustion and reduced thermal efficiency under lean-burn conditions but with relatively lower NOx emissions. This study demonstrates that secondary jet-guided combustion can effectively enhance hydrogen engine performance by optimizing mixture stratification and flame propagation providing theoretical support for clean and efficient combustion.

To ensure the safe and reliable operation of hydrogen-blended natural gas (HBNG) pipelines in urban utility tunnels this study conducted a comprehensive CFD simulation of the leakage and diffusion characteristics of HBNG in confined underground environments. Utilizing ANSYS CFD software (2024R1) a three-dimensional physical model of a utility tunnel was developed to investigate the influence of key parameters such as leak sizes (4 mm 6 mm and 8 mm)—selected based on common small-orifice defects in utility tunnel pipelines (e.g. corrosion-induced pinholes and minor mechanical damage) and hydrogen blending ratios (HBR) ranging from 0% to 20%—a range aligned with current global HBNG demonstration projects (e.g. China’s “Medium-Term and Long-Term Plan for Hydrogen Energy Industry Development”) and ISO standards prioritizing 20% as a technically feasible upper limit for existing infrastructure on HBNG diffusion behavior. The study also evaluated the adequacy of current accident ventilation standards. The findings show that as leak orifice size increases the diffusion range of HBNG expands significantly with a 31.5% increase in diffusion distance and an 18.5% reduction in alarm time as the orifice diameter grows from 4 mm to 8 mm. Furthermore hydrogen blending accelerates gas diffusion with each 5% increase in HBR shortening the alarm time by approximately 1.6 s and increasing equilibrium concentrations by 0.4% vol. The current ventilation standard (12 h−1 ) was found to be insufficient to suppress concentrations below the 1% safety threshold when the HBR exceeds 5% or the orifice diameter exceeds 4 mm—thresholds derived from simulations showing that under 12 h−1 ventilation equilibrium concentrations exceed the 1% safety threshold under these conditions. To address these gaps this study proposes an adaptive ventilation strategy that uses variable-frequency drives to adjust ventilation rates in real time based on sensor feedback of gas concentrations ensuring alignment with leakage conditions thereby ensuring enhanced safety. These results provide crucial theoretical insights for the safe design of HBNG pipelines and ventilation optimization in utility tunnels.

Amidst the escalating global challenges presented by climate change carbon trading mechanisms have become critical tools for driving reductions in carbon emissions and optimizing energy systems. However existing carbon trading models constrained by fixed settlement cycles face difficulties in addressing the scheduling needs of energy systems that operate across multiple time scales. To address this challenge this paper proposes an optimal scheduling methodology for hydrogen-encompassing integrated energy systems that incorporates a multi-time-scale carbon trading mechanism. The proposed approach dynamically optimizes the scheduling and conversion of hydrogen energy electricity thermal energy and other energy forms by flexibly adjusting the carbon trading cycle. It accounts for fluctuations in energy demand and carbon emissions occurring both before and during the operational day. In the day-ahead scheduling phase a tiered carbon transaction cost model is employed to optimize the initial scheduling framework. During the day scheduling phase real-time data are utilized to dynamically adjust carbon quotas and emission ranges further refining the system’s operational strategy. Through the analysis of typical case studies this method demonstrates significant benefits in reducing carbon emission costs enhancing energy efficiency and improving system flexibility.

Bio-hydrogen production (BHP) produced from renewable bio-resources is an attractive route for green energy production due to its compelling advantages of relative high efficiency cost-effectiveness and lower ecological impact. This study reviewed different BHP pathways and the most important enzymes involved in these pathways to identify technological gaps and effective approaches for process intensification in industrial applications. Among the various approaches reviewed in this study a particular focus was set on the latest methods of chemicals/metal addition for improving hydrogen generation during dark fermentation (DF) processes; the up-to-date findings of different chemicals/metal addition methods have been quantitatively evaluated and thoroughly compared in this paper. A new efficiency evaluation criterion is also proposed allowing different BHP processes to be compared with greater simplicity and validity

The widespread penetration of hydrogen in mainstream energy systems requires hydrogen production processes to be economically competent and environmentally efficient. Hydrogen if produced efficiently can play a pivotal role in decarbonizing the global energy systems. Therefore this study develops a framework which evaluates hydrogen production processes and quantifies deficiencies for improvement. The framework integrates slack-based data envelopment analysis (DEA) with fuzzy analytical hierarchy process (FAHP) and fuzzy technique for order of preference by similarity to ideal solution (FTOPSIS). The proposed framework is applied to prioritize the most efficient and sustainable hydrogen production in Pakistan. Eleven hydrogen production alternatives were analyzed under five criteria including capital cost feedstock cost O&M cost hydrogen production and CO2 emission. FAHP obtained the initial weights of criteria while FTOPSIS determined the ultimate weights of criteria for each alternative. Finally slack-based DEA computed the efficiency of alternatives. Among the 11 three alternatives (wind electrolysis PV electrolysis and biomass gasification) were found to be fully efficient and therefore can be considered as sustainable options for hydrogen production in Pakistan. The rest of the eight alternatives achieved poor efficiency scores and thus are not recommended.

Numerical simulations reveal the combustion dynamics of hydrogen-blended natural gas (H-BNG) in semi-open spaces. In the typical semi-open space scenario increasing the hydrogen blending ratio from 0% to 60% elevates peak internal pressure by 107% (259.3 kPa → 526.0 kPa) while reducing pressure rise time by 56.5% (95.8 ms → 41.7 ms). A vent size paradox emerges: 0.5 m openings generate 574.6 kPa internal overpressure whereas 2 m openings produce 36.7 kPa external overpressure. Flame propagation exhibits stabilized velocity decay (836 m/s → 154 m/s 81.6% reduction) at hydrogen concentrations ≥30% within 2–8 m distances. In street-front restaurant scenarios 80% H-BNG leaks reach alarm concentration (0.8 m height) within 120 s with sensor response times ranging from 21.6 s (proximal) to 40.2 s (distal). Forced ventilation reduces hazard duration by 8.6% (151 s → 138 s) while door status shows negligible impact on deflagration consequences (412 kPa closed vs. 409 kPa open) maintaining consistent 20.5 m hazard radius at 20 kPa overpressure threshold. These findings provide crucial theoretical insights and practical guidance for the prevention and management of H-BNG leakage and explosion incidents.

Hydrogen energy characterized by its abundant resources green and lowcarbon attributes and wide-ranging applications is a critical energy source for achieving carbon peaking and carbon neutrality goals. The operational efficiency of the hydrogen energy industrial chain is pivotal in determining the security of its supply chain and its contribution to China’s energy transition. This study investigates the efficiency of China’s hydrogen energy industrial chain by selecting 30 listed companies primarily engaged in hydrogen energy as the research sample. A three-stage data envelopment analysis (DEA) model is applied to assess the industry’s comprehensive technical efficiency pure technical efficiency and scale efficiency. Additionally kernel density estimation is utilized to analyze efficiency trends over time. Key factors influencing efficiency are identified and targeted recommendations are provided to enhance the performance and sustainability of the hydrogen energy industrial chain. These findings offer valuable insights to support the development and resilience of China’s hydrogen energy industry

This paper presents an improved Equivalent Consumption Minimization Strategy (ECMS) designed to optimize energy management for the hybrid hydrogen fuel power setups in multirotor drones. The proposed strategy aims to reduce hydrogen consumption and enhance the performance of the system consisting of Proton Exchange Membrane Fuel Cells (PEMFCs) and lithium batteries. Multirotor drones experience rapid power fluctuations due to their agile maneuvering but PEMFCs are unable to meet these demands swiftly due to their inherent limitations. To address this lithium batteries supplement peak power requirements and absorb excess energy on the DC bus. However this can lead to energy loss if the batteries are charged when not required. Our improved ECMS considers these inefficiencies and adjusts energy distribution to reduce hydrogen consumption and optimize the system’s performance. The proposed strategy effectively maintains the lithium batteries’ State of Charge (SOC) reduces hydrogen usage and enhances overall system efficiency when compared to traditional ECMS approaches.

Biogas (primarily biomethane) as a carbon-neutral renewable energy source holds great potential to replace fossil fuels for sustainable hydrogen production. Conventional biogas reforming systems adopt strategies similar to industrial natural gas reforming posing challenges such as high temperatures high energy consumption and high system complexity. In this study we propose a novel multi-product sequential separation-enhanced reforming method for biogas-derived hydrogen production which achieves high H2 yield and CO2 capture under mid-temperature conditions. The effects of reaction temperature steam-to-methane ratio and CO2/CH4 molar ratio on key performance metrics including biomethane conversion and hydrogen production are investigated. At a moderate reforming temperature of 425 ◦C and pressure of 0.1 MPa the conversion rate of CH4 in biogas reaches 97.1% the high-purity hydrogen production attains 2.15 mol-H2/mol-feed and the hydrogen yield is 90.1%. Additionally the first-law energy conversion efficiency from biogas to hydrogen reaches 65.6% which is 11 percentage points higher than that of conventional biogas reforming methods. The yield of captured CO2 reaches 1.88 kg-CO2/m3 -feed effectively achieving near-complete recovery of green CO2 from biogas. The mild reaction conditions allow for a flexible integration with industrial waste heat or a wide selection of other renewable energy sources (e.g. solar heat) facilitating distributed and carbonnegative hydrogen production.

Effective water management is crucial for the optimal performance and durability of proton exchange membrane fuel cells (PEMFCs) in automotive applications. Conventional techniques like electrochemical impedance spectroscopy (EIS) face challenges in accurately measuring high-frequency resistance (HFR) impedance during dynamic vehicle operations. This study proposes a novel stack water management stability control and vehicle energy control method to address these limitations. Simulation and experimental results demonstrate improved system and powertrain efficiency extended stack lifespan and optimized hydrogen consumption. These findings contribute to advancing robust water management strategies supporting the transition toward sustainable zero-emission fuel cell vehicles.

Against the backdrop of ever‑increasing energy demand and growing awareness of en‑ vironmental protection the research and optimization of hydrogen‑related multi‑energy systems have become a key and hot issue due to their zero‑carbon and clean characteristics. In the scheduling of such multi‑energy systems a typical problem is how to describe and deal with the uncertainties of multiple types of energy. Scenario‑based methods and ro‑ bust optimization methods are the two most widely used methods. The first one combines probability to describe uncertainties with typical scenarios and the second one essentially selects the worst scenario in the uncertainty set to characterize uncertainties. The selection of these scenarios is essentially a trade‑off between the economy and robustness of the so‑ lution. In this paper to achieve a better balance between economy and robustness while avoiding the complex min‑max structure in robust optimization we leverage artificial in‑ telligence (AI) technology to generate enough scenarios from which economic scenarios and feasible scenarios are screened out. While applying a simple single‑layer framework of scenario‑based methods it also achieves both economy and robustness. Specifically first a Transformer architecture is used to predict uncertainty realizations. Then a Gener‑ ative Adversarial Network (GAN) is employed to generate enough uncertainty scenarios satisfying the actual operation. Finally based on the forecast data the economic scenar‑ ios and feasible scenarios are sequentially screened out from the large number of gener‑ ated scenarios and a balance between economy and robustness is maintained. On this ba‑ sis a multi‑energy collaborative optimization method is proposed for a hydrogen‑based multi‑energy microgrid with consideration of the coupling relationships between energy sources. The effectiveness of this method has been fully verified through numerical exper‑ iments. Data show that on the premise of ensuring scheduling feasibility the economic cost of the proposed method is 0.67% higher than that of the method considering only eco‑ nomic scenarios. It not only has a certain degree of robustness but also possesses good economic performance.

N-type sulfide semiconductors are promising photocatalysts due to their broad visible-light absorption facile synthesis and chemical diversity. However photocorrosion and limited electron transport in one-step excitation and solid-state Z-scheme systems hinder efficient overall water splitting. Liquidphase Z-schemes offer a viable alternative but sluggish mediator kinetics and interfacial side reactions impede their construction. Here we report a stable Z-scheme system integrating n-type CdS and BiVO₄ with a [Fe(CN)₆]³⁻/[Fe(CN)₆]⁴⁻ mediator achieving 10.2% apparent quantum yield at 450 nm with stoichiometric H₂/O₂ evolution. High activity reflects synergies between Pt@CrOx and Co3O4 cocatalysts on CdS and cobalt-directed facet asymmetry in BiVO₄ resulting in matched kinetics for hydrogen and oxygen evolution in a reversible mediator solution. Stability is dramatically improved through coating CdS and BiVO4 with different oxides to inhibit Fe4[Fe(CN)6]3 precipitation and deactivation by a hitherto unrecognized mechanism. Separate hydrogen and oxygen production is also demonstrated in a twocompartment reactor under visible light and ambient conditions. This work unlocks the long-sought potential of n-type sulfides for efficient durable and safe solar-driven hydrogen production.

Aiming at resolving the problem of stable and efficient operation of integrated green hydrogen production storage and supply hydrogen refueling stations at different time scales this paper proposes a multi-time-scale hierarchical energy management strategy for integrated green hydrogen production storage and supply hydrogen refueling station (HFS). The proposed energy management strategy is divided into two layers. The upper layer uses the hourly time scale to optimize the operating power of HFS equipment with the goal of minimizing the typical daily operating cost and proposes a parameter adaptive particle swarm optimization (PSA-PSO) solution algorithm that introduces Gaussian disturbance and adaptively adjusts the learning factor inertia weight and disturbance step size of the algorithm. Compared with traditional optimization algorithms it can effectively improve the ability to search for the optimal solution. The lower layer uses the minute-level time scale to suppress the randomness of renewable energy power generation and hydrogen load consumption in the operation of HFS. A solution algorithm based on stochastic model predictive control (SMPC) is proposed. The Latin hypercube sampling (LHS) and simultaneous backward reduction methods are used to generate and reduce scenarios to obtain a set of high-probability random variable scenarios and bring them into the MPC to suppress the disturbance of random variables on the system operation. Finally real operation data of a HFS in southern China are used for example analysis. The results show that the proposed energy management strategy has a good control effect in different typical scenarios.

This study systematically investigates the fracture behavior of X80 pipeline steel welded joints under hydrogen-induced cracking (HIC) conditions through combined experimental characterization and numerical simulation. Microstructural observations and Vickers hardness testing reveal significant heterogeneity in the base metal heat-affected zone (HAZ) and weld metal (WM) resulting in spatially non-uniform mechanical properties. A userdefined subroutine (USDFLD) was employed to assign continuous material property distributions within the finite element model accurately capturing mechanical heterogeneity and its influence on crack-tip mechanical fields and crack propagation paths. Results show that welding thermal cycles induce pronounced microstructural evolution significantly altering hardness and strength distributions which in turn affect the evolution of crack-tip stress and plastic strain fields. Crack propagation preferentially occurs toward regions of higher yield strength where limited plasticity leads to intensified cracktip stress concentration accelerating crack growth and extending propagation paths. Moreover crack growth is accompanied by local unloading near the crack tip reducing peak stress and strain compared to the initial stationary crack tip. The stress and strain field reconfiguration are primarily localized near the crack tip while the far-field mechanical response remains largely stable.

Hydrogen gas is a promising clean-energy vector that can alleviate the current imbalance between energy supply and demand diversify the energy portfolio and underpin the sustainable development of oil and gas resources. This study pinpoints the factors that govern hydrogen quantification by pulsed-neutron logging. Monte Carlo simulations were performed to map the spatial distribution of capture γ-rays in formations saturated with either water or hydrogen and to systematically assess the effects of pore-fluid composition hydrogen density gas saturation lithology and borehole-fluid type. The results show that the counts of capture γ-rays are litter in hydrogen-bearing formations. For lowto moderate-porosity rocks the dynamic response window for hydrogensaturated pores is approximately 10% wider than that for methane-saturated pores. Increasing hydrogen density or decreasing gas saturation raises the capture-γ ratio while narrowing the dynamic range. Changes in borehole fluid substantially affect the capture-γ ratio yet have only a minor impact on the dynamic range. Lithology imposes an additional control: serpentinite enriched in structural water generates markedly higher capture-γ ratios that may complicate the quantitative evaluation of hydrogen.

Proliferation of co-located petrol-hydrogen fueling stations is an effective solution for widespread deployment of hydrogen as a transportation fuel. Such combined fueling stations largely rely on existing infrastructure hence represent a low-cost option for setting up hydrogen fueling facilities. However optimizing the layout of dual petrol-hydrogen fueling stations and their rational site selection is critical for ensuring the efficient use of re sources. This paper investigates the site selection of combined hydrogen and petrol fueling stations at the ter minus of China’s "West-to-East Hydrogen Pipeline" project. A weighting model based on EWM-CRITIC-Game Theory is developed and the weight coefficients derived from game theory are used to perform the compre hensive ranking of potential sites. The combined evaluation results yield an overall ranking of A9 > A4 > A8 > A26 > A20 > A21 > A11. The effectiveness of this novel method is verified by comparing the results with those obtained from Copeland Borda Average and geometric mean methods. Considering the actual distance con straints the final site ranking is A9 > A4 > A8 > A20 > A21 > A11 > A14. This location offers optimal con ditions for infrastructure integration and hydrogen fueling service coverage. The reliability analysis indicates that the proposed game theory-based method delivers strong performance across various scenarios underscoring its reliability and versatility in consistently delivering accurate results.

Hydrogen production from electrolytic water based on Renewable Energy has been found as a vital method for the local consumption of new energy and the utilization of hydrogen energy. In this paper the hydrogen production power supply matching the working characteristics of electrolytic water production was investigated. Through the analysis of the correlation between the electrolysis current and temperature of the proton exchange membrane electrolyzer and the electrolyzer port voltage energy efficiency and hydrogen production speed it was concluded that the hydrogen production power supply should be characterized by low output current ripple high output current and wide range voltage output. To meet the requirements of the system of hydrogen production from electrolytic water based on new energy a hydrogen production power supply scheme was proposed based on Y which is the type three is the phase staggered parallel LLC topology. In the proposed scheme the cavity with three is the phase staggered parallel output is resonated to meet the operating characteristics (high current and low ripple) of the electrolyzer and pulse frequency control is adopted to achieve resonant soft in the switching operation and increase conversion efficiency. Lastly a simulation model and a 6kW experimental prototype were built to verify the rationality and feasibility of the proposed scheme.

Methanol steam reforming (MSR) represents a highly promising pathway for sustainable hydrogen production due to its favorable hydrogen-to-carbon ratio and relatively low operating temperatures. The performance of the MSR process is strongly dependent on the selection and rational design of catalysts which govern methanol conversion hydrogen selectivity and the suppression of undesired side reactions such as carbon monoxide formation. Moreover advancements in reactor configuration and thermal management strategies play a vital role in minimizing heat loss and enhancing heat and mass transfer efficiency. Effective carbon monoxide removal technologies are indispensable for obtaining high-purity hydrogen particularly for applications sensitive to CO contamination. This review systematically summarizes recent progress in catalyst development reactor design and gas purification technologies for MSR. In addition the key technical challenges and potential future directions of the MSR process are critically discussed. The insights provided herein are expected to contribute to the development of more efficient stable and scalable MSR-based hydrogen production systems.

Underground hydrogen storage has gained interest in recent years due to the enormous demand for clean energy. Hydrogen is more diffusive than air with a smaller density and lower viscosity. These unique properties introduce distinctive hydrodynamic phenomena in hydrogen storage one of which is fingering. Fingering could induce the fluid trapped in small clusters of pores leading to a dramatic decrease in hydrogen saturation and a lower recovery rate. In this study numerical simulations are performed at the microscopic scale to understand the evolution of hydrogen saturation and the impacts of injection and withdrawal cycles. Two sets of micromodels with different porosity (0.362 and 0.426) and minimum sizes of pore throats (0.362 mm and 0.181 mm) are developed in the numerical model. A parameter analysis is then conducted to understand the influence of injection velocity (in the range of 10-2 m/s to 10-5 m/s) and porous structure on the fingering pattern followed by an image analysis to capture the evolution of the fingering pattern. Viscous fingering capillary fingering and crossover fingering are observed and identified under different boundary conditions. The fractal dimension specific area mean angle and entropy of fingers are proposed as geometric descriptors to characterize the shape of the fingering pattern. When porosity increases from 0.362 to 0.426 the saturation of hydrogen increases by 26.2%. Narrower pore throats elevate capillary resistance which hinders fluid invasion. These results underscore the importance of pore structures and the interaction between viscous and capillary forces for hydrogen recovery efficiency. This work illuminates the influence of the pore structures and the fluid properties on the immiscible displacement of hydrogen and can be further extended to optimize the injection strategy of hydrogen in underground hydrogen storage.

Hydrogen-powered unmanned aerial vehicles (UAVs) offer significant advantages such as environmental sustainability and extended endurance demonstrating broad application prospects. However the hydrogen fuel cells face prominent thermal management challenges during flight operations. This study established a numerical model of the fuel cell thermal management system (TMS) for a hydrogen-powered UAV. Computational fluid dynamics (CFD) simulations were subsequently performed to investigate the impact of various design parameters on cooling performance. First the cooling performance of different fan density configurations was investigated. It was found that dispersed fan placement ensures substantial airflow through the peripheral flow channels significantly enhancing temperature uniformity. Specifically the nine-fan configuration achieves an 18.5% reduction in the temperature difference compared to the four-fan layout. Additionally inlets were integrated with the fan-based cooling system. While increased external airflow lowers the minimum fuel cell temperature its impact on high-temperature zones remains limited with a temperature difference increase of more than 19% compared to configurations without inlets. Furthermore the middle inlet exhibits minimal vortex interference delivering superior thermal performance. This configuration reduces the maximum temperature and average temperature by 9.1% and 22.2% compared to the back configuration.

Photocatalytic membrane reactors (PMRs) which combine photocatalysis with membrane separation represent a pivotal technology for sustainable water treatment and resource recovery. Although extensive research has documented various configurations of photocatalytic-membrane hybrid processes and their potential in water treatment applications a comprehensive analysis of the interrelationships among reactor architectures intrinsic physicochemical mechanisms and overall process efficiency remains inadequately explored. This knowledge gap hinders the rational design of highly efficient and stable reactor systems—a shortcoming that this review seeks to remedy. Here we critically examine the connections between reactor configurations design principles and cutting-edge applications to outline future research directions. We analyze the evolution of reactor architectures relevantreaction kinetics and key operational parameters that inform rational design linking these fundamentals to recent advances in solar-driven hydrogen production CO2 conversion and industrial scaling. Our analysis reveals a significant disconnect between the mechanistic understanding of reactor operation and the system-level performance required for innovative applications. This gap between theory and practice is particularly evident in efforts to translate laboratory success into robust and economically feasible industrial-scale operations. We believe that PMRs willrealize theirtransformative potential in sustainable energy and environmental applications in future.

Environmental pollution caused by shipping has always received great attention from the international community. Currently due to the difficulty of fully electrifying medium- and large-scale ships the hybrid energy ship power system (HESPS) will be the main type in the future. Considering the economic and long-term energy efficiency of ships as well as the uncertainty of the output power of renewable energy units this paper proposes an improved design for an integrated power system for large cruise ships combining renewable energy and a hybrid energy storage system. An energy management strategy (EMS) based on time-gradient control and considering load dynamic response as well as an energy storage power allocation method that considers the characteristics of energy storage devices is designed. A bi-level power capacity optimization model grounded in comprehensive scenario planning and aiming to optimize maximum return on equity is constructed and resolved by utilizing an improved particle swarm optimization algorithm integrated with dynamic programming. Based on a large-scale cruise ship the aforementioned method was investigated and compared to the conventional planning approach. It demonstrates that the implementation of this optimization method can significantly decrease costs enhance revenue and increase the return on equity from 5.15% to 8.66%.