China, People’s Republic

This study employs first principles calculations and thermodynamic analyses to investigate the dissociative adsorption of hydrogen on the Fe(110) surface. The results show that the adsorption energies of hydrogen at different sites on the iron surface are −1.98 eV (top site) −2.63 eV (bridge site) and −2.98 eV (hollow site) with the hollow site being the most stable adsorption position. Thermodynamic analysis further reveals that under operational conditions of 25 ◦C and 12 MPa the Gibbs free energy change (∆G) for hydrogen dissociation is −1.53 eV indicating that the process is spontaneous under pipeline conditions. Moreover as temperature and pressure increase the spontaneity of the adsorption process improves thus enhancing hydrogen transport efficiency in pipelines. These findings provide a theoretical basis for optimizing hydrogen transport technology in natural gas pipelines and offer scientific support for mitigating hydrogen embrittlement improving pipeline material performance and developing future hydrogen transportation strategies and safety measures.

Hydrogen blending in natural gas pipelines facilitates renewable energy integration and cost-effective hydrogen transport. Due to hydrogen’s lower density and higher leakage potential compared to natural gas understanding hydrogen concentration distribution is critical. This study employs ANSYS Fluent 2022 R1 with a realizable k-ε model to analyze flow dynamics of hydrogen–methane mixtures in horizontal and undulating pipelines. The effects of hydrogen blending ratios pressure (3–8 MPa) and pipeline geometry were systematically investigated. Results indicate that in horizontal pipelines hydrogen concentrations stabilize near initial values across pressure variations with minimal deviation (maximum increase: 1.6%). In undulating pipelines increased span length of elevated sections reduces maximum hydrogen concentration while maintaining proximity (maximum increase: 0.65%) to initial levels under constant pressure. Monitoring points exhibit concentration fluctuations with changing pipeline parameters though no persistent stratification occurs. However increasing the undulating height elevation difference leads to an increase in the maximum hydrogen concentration at the top of the pipeline rising from 3.74% to 9.98%. The findings provide theoretical insights for safety assessments of hydrogen–natural gas co-transport and practical guidance for pipeline design optimization.

Underground hydrogen storage in aquifers is a promising solution to address the imbalance between energy supply and demand yet its practical implementation requires optimized strategies to ensure high efficiency and economic viability. To improve the storage and production efficiency of hydrogen it is essential to select the appropriate cushion gas and to study the influence of reservoir and process parameters. Based on the conceptual model of aquifer with single-well injection and production three potential cushion gas (carbon dioxide nitrogen and methane) were studied and the changes in hydrogen recovery for each cushion gas were compared. The effects of temperature initial pressure porosity horizontal permeability vertical to horizontal permeability ratio permeability gradient hydrogen injection rate and hydrogen production rate on the purity of recovered hydrogen were investigated. Additionally the impact of different well pattern on the purity of recovered hydrogen was studied. The results indicate that methane is the most effective cushion gas for improving hydrogen recovery in UHS. Different well patterns have significant impacts on the purity of recovered hydrogen. The mole fractions of methane in the produced gas for the single-well line-drive pattern and five-spot pattern were 16.8% 5% and 3.05% respectively. Considering the economic constraints the five-spot well pattern is most suitable for hydrogen storage in aquifers. Reverse rhythm reservoirs with smaller permeability differences should be chosen to achieve relatively high hydrogen recovery and purity of recovered hydrogen. An increase in hydrogen production rate leads to a significant decrease in the purity of the recovered hydrogen. In contrast hydrogen injection rate has only a minor effect. These findings provide actionable guidance for the selection of cushion gas site selection and operational design of aquifer-based hydrogen storage systems contributing to the large-scale seasonal storage of hydrogen and the balance of energy supply and demand.

The use of rare earth elements in hydrogen storage processes offers significant advantages in terms of increasing technological efficiency and ensuring system security. However this process also creates some serious problems in terms of environmental and economic sustainability. It is necessary to determine the most critical indicators affecting the sustainable use of these elements. Studies on this subject in the literature are quite limited and this may lead to wrong investment decisions. The main purpose of this study is to determine the most important indicators to increase the sustainable use of rare earth elements in hydrogen storage processes. An original decision-making model in which Siamese network logarithmic percentage-change driven objective weighting (LOPCOW) fractal fuzzy numbers and weighted influence super matrix with precedence (WISP) approaches are integrated in the study. This study provides an original contribution to the literature by identifying the most critical indicators affecting the sustainable use of rare earths in hydrogen storage processes by presenting an innovative model. Fractal structures such as Koch Snowflake Cantor Dust and Sierpinski Triangle can model complex uncertainties more successfully. Fractal structures are particularly effective in modeling linguistic fuzziness because their recursive nature closely mirrors the layered and imprecise way humans often express subjective judgments. Unlike linear fuzzy sets fractals can capture the patterns of ambiguity found in expert evaluations. Hydrogen storage capacity and government supports are determined as the most vital criteria affecting sustainability in rare earth use.

Driven by the global energy transition and the dual carbon goals developing low-carbon and zero-carbon alternative fuels has become a core issue for sustainable development in the internal combustion engine sector. Ammonia is a promising zero-carbon fuel with broad application prospects. However its inherent combustion characteristics including slow flame propagation high ignition energy and narrow flammable range limit its use in internal combustion engines necessitating the addition of auxiliary fuels. To address this issue this paper proposes a composite injection technology combining “ammonia duct injection + hydrogen cylinder direct injection.” This technology utilizes highly reactive hydrogen to promote ammonia combustion compensating for ammonia’s shortcomings and enabling efficient and smooth engine operation. This study based on bench testing investigated the effects of hydrogen direct injection timing (180 170 160 150 140◦ 130 120 ◦CA BTDC) hydrogen direct injection pressure (4 5 6 7 8 MPa) on the combustion and emissions of the ammonia–hydrogen engine. Under hydrogen direct injection timing and hydrogen direct injection pressure conditions the hydrogen mixture ratios are 10% 20% 30% 40% and 50% respectively. Test results indicate that hydrogen injection timing that is too early or too late prevents the formation of an optimal hydrogen layered state within the cylinder leading to prolonged flame development period and CA10-90. The peak HRR also exhibits a trend of first increasing and then decreasing as the hydrogen direct injection timing is delayed. Increasing the hydrogen direct injection pressure to 8 MPa enhances the initial kinetic energy of the hydrogen jet intensifies the gas flow within the cylinder and shortens the CA0-10 and CA10-90 respectively. Under five different hydrogen direct injection ratios the CA10- 90 is shortened by 9.71% 11.44% 13.29% 9.09% and 13.42% respectively improving the combustion stability of the ammonia–hydrogen engine.

Green hydrogen is emerging as a pivotal energy carrier in the global transition toward decarbonization offering a sustainable alternative to fossil fuels in sectors such as heavy industry transportation power generation and long-duration energy storage. Despite its potential large-scale deployment remains hindered by significant economic technological and infrastructure challenges. Current production costs for green hydrogen range from USD 3.8 to 11.9/kg H2 significantly higher than gray hydrogen at USD 1.5–6.4/kg H2 due to high electricity prices and electrolyzer capital costs exceeding USD 2000 per kW. This review critically examines the key bottlenecks in green hydrogen production focusing on water electrolysis technologies electrocatalyst limitations and integration with renewable energy sources. The economic viability of green hydrogen is constrained by high electricity consumption capital-intensive electrolyzer costs and operational inefficiencies making it uncompetitive with fossil fuel-based hydrogen. Infrastructure and supply chain challenges including limited hydrogen storage transport complexities and critical material dependencies further restrict market scalability. Additionally policy and regulatory gaps disparities in financial incentives and the absence of a standardized certification framework hinder international trade and investment in green hydrogen projects. This review also highlights market trends and global initiatives assessing the role of government incentives and cross-border collaborations in accelerating hydrogen adoption. While technological advancements and cost reductions are progressing overcoming these challenges requires sustained innovation stronger policy interventions and coordinated efforts to develop a resilient scalable and cost-competitive green hydrogen sector.

Hydrogen fuel cell vehicles (HFCVs) are vital for advancing the hydrogen economy and decarbonizing the transportation sector. However research on HFCV market dynamics in passenger vehicles is limited especially incorporating both market competition from other vehicle types and the comprehensive supply–demand market dynamics. To bridge this gap our study proposed a spatial agent-based model to simulate the HFCV market evolution with the aim of finding effective strategies and policy implications for breaking the diffusion dilemma of the HFCV market. We calibrated the model using survey data (N=1065) collected from Beijing and evaluated its performance across five “What-If” scenarios. Results indicate that HFCVs and hydrogen stations are difficult to penetrate under the current conditions despite HFCV applicants and market share growing by 37.5% and 15.63% respectively. Consumer perceptions on cost social and environment have greater impacts on HFCV proliferation than facility availability. The HFCV purchase subsidy has much greater impact than the technological learning rate greatly accelerating its market emergence timing. Finally HFCVs’ diffusion significantly influences the market of battery electric vehicles.

Ocean islands possess abundant renewable energy resources providing favorable conditions for developing offshore clean energy microgrids. However geographical isolation poses significant challenges for direct energy transfer between islands. Recent electrolysis and hydrogen storage technology advancements have created new opportunities for distributed energy utilization in these remote areas. This paper presents a low-carbon economic dispatch strategy designed explicitly for distant oceanic islands incorporating energy self-sufficiency rates and seasonal hydrogen storage (SHS). We propose a power supply model for offshore islands considering hydrogen production from offshore wind power. The proposed model minimizes operational and carbon emission costs while maximizing energy self-sufficiency. It considers the operational constraints of the island’s energy system the offshore transportation network the hydrogen storage infrastructure and the electricityhydrogen-transportation coupling of hydrogen storage (HS) and seasonal hydrogen storage (SHS) services. To optimize the dispatch process this study employs an improved Grey Wolf Optimizer (IGWO) combined with the Differential Evolution method to enhance population diversity and refine the position updating mechanism. Simulation results demonstrate that integrating HS and SHS effectively enhances energy self-sufficiency and reduces carbon emissions. For instance hydrogenation costs decreased by 21.4% after optimization and the peak-valley difference was reduced by 16%. These findings validate the feasibility and effectiveness of the proposed approach.

Currently there are many gaps in the research on the safety of hydrogen-powered trains and the hazardous points vary across different scenarios. It is necessary to conduct safety analysis for various scenarios in order to develop effective accident response strategies. Considering the implementation of hydrogen power in the rail transport sector this paper reviews the development status of hydrogen-powered trains and the hydrogen leak hazard chain. Based on the literature and industry data a thorough analysis is conducted on the challenges faced by hydrogen-powered trains in the scenario of electrified railways tunnels train stations hydrogen refueling stations and garages. Existing railway facilities are not ready to deal with accidental hydrogen leakage and the promotion of hydrogen-powered trains needs to be cautious.

Introduction: With the increasing demand for energy utilization efficiency and minimization of environmental carbon emissions in industrial parks optimizing the configuration and scheduling of integrated energy systems has become crucial. This study focuses on integrated energy systems with massive flexible load resources aiming to maximize energy utilization efficiency while reducing environmental impact. Methods: To model the uncertainties in wind and solar power outputs we employed three-parameter Weibull distribution models and Beta distribution models. Flexible loads were categorized into three types to match different electricity consumption patterns. Additionally an enhanced Kepler Optimization Algorithm (EKOA) was proposed incorporating chaos mapping and adaptive learning rate strategies to improve search scope convergence speed and solution efficiency. The effectiveness of the proposed optimization scheduling and configuration methods was validated through a case study of an industrial park located in a coastal area of southeastern China. Results: The results show that using three-parameter Weibull distribution models and Beta distribution models more accurately reflects the variations in actual wind speeds and solar irradiance levels achieving peak shaving and valley filling effects and enhancing renewable energy utilization. The EKOA algorithm significantly reduced curtailment rates of wind and solar power generation while achieving substantial economic benefits. Compared with other operation modes of hydrogen the daily average cost is reduced by 12.92% and external electricity purchases are reduced by an average of 20.2 MW h/day. Discussion: Although our approach shows potential in improving energy utilization efficiency and economic gains this paper only considered hydrogen energy for single-use pathways and did not account for the economic benefits from selling hydrogen in the market. Future research will further incorporate hydrogen demand response mechanisms and optimize the output of integrated energy systems from the perspective of spot markets. These findings provide valuable references for relevant engineering applications.