Hydrogen

Green hydrogen—hydrogen produced from renewable electricity—is central to global decarbonization strategies. However, despite their fragile governance, damaged infrastructure, water scarcity, and limited investment security, conflict-affected developing economies remain largely absent from hydrogen research. This study addresses that gap by developing and validating a multi-evidence strategic framework for green-hydrogen (GH₂) adoption in fragile institutional environments, using Palestine as a challenging test case. Methodologically speaking, the framework integrates four evidence streams—barrier prioritization by 45 Palestinian experts using the Analytic Hierarchy Process (AHP); structural modeling of barrier–adoption–sustainability relationships using partial least squares structural equation modeling (PLS-SEM); strategic-pathway ranking using the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS); and an original Sustainable Development Goal (SDG) Contribution Index—externally validated by an independent panel of 120 energy experts across 18 Middle East and North Africa (MENA) countries. Three findings stand out. Firstly, expert perception and structural evidence diverge: technical barriers receive the highest expert weight (56.2%) yet show the weakest structural effect on adoption (β = −0.230), whereas social barriers, weighted lowest by experts (4.8%), rank second in predictive power (β = −0.310). Secondly, Small-Scale Community Production is the most robust deployment pathway, ranked first under every weighting scenario tested. Thirdly, government policy quality acts as a governance multiplier, raising the sustainability returns of adoption by 20.2%, with benefits concentrated in SDGs 7, 13, 8, and 9. Practically speaking, the framework yields seven strategic goals and a phased 2026–2040 roadmap for fragile developing economies. Full article

The growing demand for sustainable energy carriers has intensified interest in hydrogen production from renewable resources and waste-derived substrates. In this context, microbial electrolysis cells (MECs) have emerged as a promising technology for the simultaneous treatment of organic waste and biohydrogen generation. This review provides an overview of recent advances in MEC systems, focusing on reactor configurations, performance indicators such as hydrogen production rate, coulombic efficiency, and chemical oxygen demand removal. Attention is given to the valorization of real waste streams, including municipal and agro-industrial effluents, highlighting the differences between laboratory- and pilot-scale applications. While numerous studies have demonstrated the technical feasibility of MECs, several bottlenecks still limit their large-scale implementation, including challenges associated with the use of complex substrates. In particular, untreated wastewater often leads to reduced process efficiency due to its variable composition and the occurrence of competing microbial pathways. To overcome these limitations, integrated approaches are also discussed, with emphasis on the coupling of dark fermentation, capable of enhancing substrate biodegradability through the production of volatile fatty acids, with MEC systems. Overall, MEC technology represents a promising pathway for sustainable hydrogen production within circular waste management frameworks, although further advancements are required to enable its practical application. Full article

To improve the sluggish low-temperature hydrogen storage kinetics of RE-Mg-based alloys, Bi₂O₃ is introduced into CeMg₁₁Ni as a functional dopant for microstructural regulation, and CeMg₁₁Ni + x wt.% Bi₂O₃ (x = 0, 3, 5, 7, 10) composites are fabricated through planetary ball milling. Multiple characterization methods including XRD, SEM and TEM were used to explore the effects of Bi₂O₃ on the microstructure and hydrogen storage properties. Bi₂O₃ maintains stable phase during cycling and does not participate in reversible hydrogen storage reactions. It cooperates with in situ formed CeH₂ nanocrystals to construct high-density interfacial defects. The 5 wt.% Bi₂O₃-doped alloy exhibits the optimal balance between exposed catalytic sites and open hydrogen diffusion channels, achieving complete dehydrogenation within 144 s at 633 K, a reduced dehydrogenation activation energy of 63.89 kJ mol⁻¹, and an 84.7% hydrogen absorption ratio within 5 min at 423 K. Bi₂O₃ has a weak effect on the thermodynamic properties of the alloy, with only a slight enthalpy change of less than 1 kJ/mol within the experimental error range. Bi₂O₃ enhances hydrogen storage reactions through a synergistic “active sites–diffusion channels” mechanism, in which oxygen vacancies promote H₂ dissociation and heterogeneous interfaces facilitate hydrogen diffusion, thereby reducing the reaction energy barrier. Full article

Fuel cell electric vehicles (FCEVs) require specific hydrogen purity, as even trace contaminants can degrade proton exchange membrane fuel cells (PEMFCs). While hydrogen quality is monitored along the supply chain according to international standards, potential contamination from in-vehicle materials, such as lubricants and greases, remains largely unexplored. Here, we present a staged testing framework consisting of (i) a rapid pre-screening for formulation stability and (ii) a full qualification pathway to assess lubricant-derived contamination under realistic refueling conditions. Candidate lubricants were exposed to hydrogen in a 700 bar Type IV vessel following an SAE J2601 refueling procedure. Contamination risks were evaluated by optical inspection, particulate matter, and gas analysis, monitoring contaminants specified in ISO 14687:2025 Grade D. The applicability of the framework was demonstrated in practical scenarios. In the pre-screening pathway, a silicone-based formulation fulfilled the 24 h acceptance criteria for formulation stability and was classified as potentially suitable for high-pressure hydrogen tank applications. In contrast, two other lubricants based on silicone and mineral oil exhibited visible changes associated with increased risk of particulate matter release, resulting in a classification of unsuitable. In the full qualification pathway, the fluorinated DuPont^TM MOLYKOTE^® HP-300 Grease was evaluated over 23 days and showed no release of harmful contaminants into the hydrogen gas, leading to the classification of suitable. Collectively, the presented protocols provide a structured basis for screening and qualifying lubricants for high-pressure hydrogen tanks in PEMFC applications, supporting future standardization in hydrogen technologies. Full article

The development of hydrogen fueling processes is an essential infrastructure component needed for the adoption of hydrogen-fueled vehicles as a transportation technology. This study provides techno-economic analysis (TEA) for two hydrogen fueling pathways (Case A, Case B), one of which (Case A) does not employ hydrogen liquefaction, while the other one (Case B) does. Both cases consider the same conditions as one another, of gaseous hydrogen inlet availability and gaseous hydrogen outlet dispensing. The TEA analysis carried out is based on data supported from the literature and process flowsheet UNISIM^® software simulations. The obtained TEA results indicate that the levelized cost of hydrogen (LCOH) of the gaseous hydrogen Case A is USD 4.20/kg H₂, which is lower than the LCOH of the liquefied hydrogen Case B, which is USD 10.14/kg H₂. Given the energy equivalence of a gallon of gasoline to kg H₂, and the higher efficiencies of hydrogen fuel cell vehicles over gasoline vehicles, the above conditions suggest that Case B fueling (with hydrogen liquefaction) involves high energy consumption and may delay the growth of hydrogen-fuel-based transportation technology, while Case A fueling (no hydrogen liquefaction) will likely become preferrable over both Case B hydrogen fueling and gasoline fueling, thus accelerating the growth of hydrogen-fuel-based transportation technology. Full article

The pearlitic microstructure, comprising alternating lamellae of ferrite and cementite, provides a favorable combination of strength, toughness, and wear resistance. Consequently, pearlitic steels have been widely utilized in pipeline systems due to their advantageous mechanical properties and cost-effectiveness. These characteristics also render pearlitic steel pipelines promising candidates for hydrogen transport infrastructure, particularly in the context of repurposing existing natural gas networks. However, interactions between hydrogen and the pearlitic microstructure raise significant concerns regarding hydrogen embrittlement, a phenomenon that can substantially degrade mechanical performance and compromise long-term structural integrity. Experimental observations indicate that pearlitic microstructures are particularly susceptible to hydrogen embrittlement, largely due to the high density of ferrite–cementite interfaces, which act as effective hydrogen trapping sites. These detrimental effects motivate the present study, which aims to develop a deeper understanding of nanoscale mechanisms of hydrogen-assisted crack initiation and propagation in pearlitic microstructures. In this work, molecular dynamics simulations are employed to investigate the initiation and propagation of hydrogen-affected cracks in pearlitic microstructures, considering lamellar orientations both parallel and perpendicular to the applied tensile loading direction. The analysis focuses on the synergistic interaction between hydrogen-enhanced decohesion (HEDE), which promotes interfacial separation due to hydrogen segregation, and hydrogen-enhanced localized plasticity (HELP). Full article

After leakage from buried hydrogen-blended natural gas pipelines, gas may seep through the soil into quasi-closed enclosures and form buoyancy-driven non-uniform combustible clouds. The effect of ignition delay on such clouds remains insufficiently understood, particularly regarding the relationship between visible flame development and local thermal response. In this study, 44 soil-seepage combustion experiments were conducted in a 1.5 m × 1.5 m × 1.5 m enclosure. The methane and hydrogen concentrations at three heights, flame evolution, and transient temperatures were measured using gas sensors, high-speed imaging, and thermocouples. The ignition delay ranged from 27 s to 5429 s, with hydrogen blending ratios of 10–30 vol% and ignition positions at the floor, middle, and ceiling levels. The results show that longer ignition delays generally weakened the visible flame luminosity and propagation extent. However, the peak temperature measured by the central thermocouple did not decrease. For the long-delay subset with t_d > 307 s, the central peak temperature increased with the ignition delay, with R² = 0.74. Concentration measurements indicated that preferential hydrogen migration and slower methane redistribution continuously reconfigured the local flammability state before ignition. These findings suggest that, in enclosed soil-seepage HBNG scenarios, prolonged ignition delay may weaken visible flame development but does not necessarily reduce local thermal exposure. Full article

Hydrogen supply chains require coordinated planning from upstream production to downstream distribution and end-user delivery; however, significant logistical challenges remain under emerging hydrogen infrastructure constraints. In particular, the transportation sector faces difficulties in achieving efficient distribution while accounting for limited hydrogen refueling availability and vehicle range restrictions. This study evaluates key network design decisions involving distribution center location and fuel cell electric vehicle (FCEV) routing while incorporating hydrogen refueling stations within the transportation system. An integrated framework is proposed by combining K-means clustering for DC location planning with a hydrogen-powered FCEV routing model. Hydrogen refueling stations are incorporated as routing constraints to ensure feasible distribution operations. Next, a case study in Thailand is conducted to validate the proposed model under realistic logistical conditions. The results illustrate how clustering-based allocation improves network coordination, while the integrated FCEV routing approach ensures feasible and efficient delivery under refueling constraints. Comparative analysis further highlights improvements in system performance and provides practical insights for designing coordinated hydrogen logistics systems across integrated supply chain networks. Full article

Steam methane reforming (SMR) powered by induction heating offers a promising route for low CO₂-emission hydrogen production, but predictive modelling remains challenging because the available experimental data are limited and heterogeneous. This study proposes a hybrid Bayesian neural network (H-BNN) to predict the mass of hydrogen (MoH) from literature-derived SMR data using operating variables including temperature, flow rate, power input, time-on-stream, and interval duration. Feedforward neural network (FNN) and classical Bayesian neural network (BNN) models were also developed as benchmarks, and all three architectures were evaluated with ReLU, Tanh, and GELU activation functions. To address data scarcity, only the training split was augmented at scales of $k=2$, 5, and 10, while the validation and test sets were kept unchanged. The H-BNN combines deterministic feature extraction with Bayesian uncertainty-aware prediction, enabling a balance between accuracy and uncertainty representation. Across the validation-selected models, test performance reached R² ∼ 0.9894 to 0.9969, with mean absolute errors of 0.0126 g to 0.0217 g. The strongest advantage appeared at k = 2, where the H-BNN outperformed the benchmark models. Overall, the proposed H-BNN is a promising framework for hydrogen prediction under data-scarce conditions, although its predictive intervals remain informative rather than fully calibrated. Full article

Transition metal-doped magnesium hydride solids are leading candidates as hydrogen storage materials. Here, a double-hybrid density functional theory method is used for the first time to explore the ground state geometries and electronic properties of small MgScH_n and MgTiH_n (n = 1–18) clusters. It is determined that hydrogen atoms aggregate to the metal core of the cluster up to a saturation limit of MgScH₁₃ and MgTiH₁₄ for each transition metal. Additional hydrogen atoms exist as weakly interacting dissociated H₂ molecules. These saturated clusters containing scandium and titanium contain a large hydrogen mass percent of 15.9% and 16.4%, respectively. A detailed discussion of cluster growth mechanisms, hydrogen dissociation pathways, the effect of each different transition metal, and the cluster stabilities is presented as determined at the DSDPBEP86/6-311++G(3df,3pd) level of theory. Full article

On-site hydrogen refueling stations (HRS) face significant operational challenges due to the stochastic nature of hydrogen demand, creating a severe supply–demand mismatch. Under traditional pressure-based hysteresis control, this volatility forces Proton Exchange Membrane (PEM) electrolyzers into frequent start–stop cycles, accelerating degradation and reducing efficiency. In response, this study introduces an automated control framework integrating macroscopic gas-state modeling with deep-learning-based demand prediction. First, a real-gas thermodynamic model was established. Monte Carlo simulations of 100 random filling scenarios identified a robust design benchmark of 4.5 kg per vehicle. A low filling stability coefficient (5.02%) confirmed that individual thermodynamic fluctuations are negligible, validating a traffic-flow-driven demand approach. Next, a deep Long Short-Term Memory (LSTM) network was developed to forecast short-term demand. Trained on an 8784 h dataset exhibiting “double-peak” traffic patterns, the model achieved high precision on the unseen test set, yielding a Root Mean Square Error (RMSE) of 6.75 kg and a normalized RMSE (nRMSE) of 0.0987, explaining 82% of the demand variance. Finally, an LSTM-informed demand-following control strategy was formulated to enable proactive, thermally bounded operation alongside a novel “Hot Standby” mechanism. Maintaining a minimal 3.0 kg/h holding current during idle periods sustains stack temperatures above 60 °C, effectively mitigating thermal stress. Comparative simulations over 1464 h demonstrated that the proposed framework reduces detrimental cold start–stop cycles by 98.4% (from 61 to 1) and suppresses power output fluctuations by 40.7% compared to the traditional baseline. These results confirm that data-driven control significantly enhances operational stability, facilitates grid integration, and extends core equipment service life. Full article

This study developed and validated a new simple and improved two-parameter high-quality equation of state (EOS) for hydrogen that can be used with less computational burden for the accurate description of various processes regarding underground hydrogen storage. Variation in hydrogen gas density with pressure was described by the modified power-law equation by relating density variation to deviations of density from the low-end and high-end limit values of density. The high-end limit density dependence on temperature was described by an Arrhenius-type asymptotic exponential function. The parameters of this EOS were determined by requiring thermodynamic consistency. This simple two-parameter EOS is thermodynamically consistent because the molar density is equal to zero, and its derivative with respect to pressure is equal to 1/(RT), like an ideal gas EOS when pressure approaches zero (T is absolute temperature, and R is the universal gas constant). This new simple EOS correlates hydrogen density efficiently using experimental data over 0–100 MPa and 220–473 K and molecular simulation data over the 14.03–116.064 MPa and 310.9–470 K ranges of pressures and temperatures. The new EOS is very accurate, as indicated by the coefficients of correlation being almost equal to unity (R² = 0.9999), the relative difference between the correlation and measured density values being very close to zero (RMSE = 0.0032), and the percentage average absolute value of the relative deviation of the EOS correlation density values ρ_EOS from the experimental density values ρ_Data being (ρ_Data/ρ_EOS − 1)100 = 0.15% average uncertainty. Full article

Heat exchanger integration is a key design consideration for engines adapted to run on hydrogen and requiring liquid hydrogen to be preheated prior to combustion. For a typical small turboshaft, a comparison is made of fuel heating via an intercooler, a recuperator, or both in combination. This steady-state, zero-dimensional thermodynamic assessment examines the overall performance effects of the heat exchanger installations, heat loads and setpoint temperatures. It shows that exhaust gas recuperation provides up to 15% SFC reduction relative to an engine using power offtake for fuel preconditioning, with an average reduction of 14% across the evaluated operating points. Fuel heating via an intercooler is constrained by off-design and low-temperature thermal management requirements, so it only gives modest SFC benefits and will reduce specific power unless the engine is substantially redesigned. Within the evaluated design space, the combined intercooled and recuperated arrangement does not provide the lowest SFC, but it offers a balanced heat load distribution that may help to mitigate the risk of local air-side icing in the heat exchangers. Unlike previous works that considered turbofan engine architectures, this study focuses on turboshaft and turbogenerator installations where shaft power objectives and operating constraints determine the relative merits of alternative heat exchanger integration strategies. It includes an assessment of potential effects on NOx emissions as well as SFC. The study provides guidance for preliminary design and sizing of heat exchangers for fuel thermal management, but analysis of transients in the cryogenic systems and detailed assessments of aircraft-level integration penalties will be specific to particular engine applications and are beyond the scope of the present study. Full article

Green hydrogen supply chain optimization requires integrated forecasting frameworks linking meteorological prediction with photovoltaic electrolyzer system performance for strategic site selection and infrastructure planning. This study develops an end-to-end XGBoost MATLAB framework to forecast and optimize solar hydrogen production across Morocco’s Atlantic coastal corridor. Extreme Gradient Boosting models trained on NASA POWER satellite data were used to predict ambient temperature and global horizontal irradiance at four coastal sites. Forecasted meteorological variables were coupled with deterministic photovoltaic and proton exchange membrane (PEM) electrolyzer simulations implemented in MATLAB. The forecasting models achieved high predictive accuracy (R² > 0.99 for temperature and R² > 0.95 for irradiance), while hydrogen production estimates maintained errors below 8% during multi-year validation. Comparative analysis identified Dakhla as the optimal site, delivering the highest annual hydrogen yield due to superior solar resource and capacity factor. The proposed framework provides a reproducible technical decision support tool for renewable hydrogen site selection and infrastructure planning. Full article

The intensifying climate problem requires substantial decarbonisation in the energy, industry, and transportation sectors, with hydrogen recognised as a crucial energy carrier. The increase in global energy consumption, driven by population growth and industrialisation, challenges the constraints of fossil fuel resources and their detrimental impact on CO₂ levels. Hydrogen, noted for its high energy density and versatility in generating power from both fossil and renewable sources, acts as a crucial supplement to direct electrification. Currently, worldwide hydrogen production exceeds 100 million tonnes per year, predominantly in the form of “grey hydrogen,” which significantly contributes to CO₂ emissions without the use of carbon capture systems. This analysis comprehensively assesses hydrogen’s contribution to decarbonisation, encompassing the entire value chain: production methods, storage options (compressed gas, liquid hydrogen, and complex hydrides), transportation techniques (pipelines, cars, rail, and ammonia carriers), and various uses. Key performance parameters indicate trade-offs concerning energy density, storage, production expenses, and transportation alternatives. Notwithstanding advancements in hydrogen technologies, obstacles persist, encompassing energy penalties, infrastructural requirements, and safety issues. This evaluation highlights the need for coordinated policies and investment to enhance hydrogen’s adaptability, ensuring alignment with direct electrification policies to achieve net-zero emissions by 2050. Full article

The transition to low-carbon hydrogen is recognized as a priority decarbonization pathway, yet the risk profiles of hydrogen projects remain poorly characterized for non-Western, resource-rich, and geopolitically constrained economies. This study develops and applies a structured expert-based risk mapping framework for low-carbon hydrogen production in Russia. The framework integrates three procedural steps: (1) identification and classification of 21 risk factors across seven thematic groups based on systematic literature analysis; (2) construction of a directed interdependency matrix (7 × 7, ordinal scale 0–2) via structured expert elicitation (n = 10, February 2026); and (3) probability–impact prioritization using the P × S scoring heuristic (both axes on a 1–5 scale, per ISO 31000:2018). Results reveal three critical risk factors (P × S Score ≥ 20): high cost of capital and restricted access to external financing (Score = 24, P = 5, S = 5), dependence on imported electrolyzer components (Score = 20, P = 4, S = 4), and insufficient export infrastructure (Score = 20, P = 5, S = 4). The interdependency matrix identifies economic and financial risks as the primary “accumulator” of systemic influence, receiving maximum incoming impact from all other six groups. Regulatory risks occupy a medium position but exert disproportionate cascading effects on technology choice and project economics. The framework is explicitly designed for transferability to other resource-abundant, capital-constrained economies (Kazakhstan, Iran, Algeria), with structural adaptation conditions specified. Findings are relevant for policymakers, investors, and multilateral stakeholders shaping hydrogen value chains in non-Western contexts. Full article

This study investigates the explosion suppression of N₂ and CO₂ on NH₃/H₂/air mixtures (NH₃:H₂ = 4:6, φ = 0.6–1.5) in a 5 L constant volume chamber. Results show that CO₂ exhibits superior efficacy compared to N₂. At φ = 1.0, the addition of 25% CO₂ reduces the maximum explosion overpressure and maximum pressure rise rate by 59.28% and 91.00%, respectively, whereas the corresponding reductions caused by 25% N₂ are 29.28% and 83.85%. The laminar burning velocity decreases continuously with increasing inhibitor concentration under all investigated conditions, and the reduction caused by CO₂ is markedly greater than that caused by N₂. Kinetic analysis indicates that the stronger suppression effect of CO₂ is mainly associated with its stronger dilution and heat-absorption effects, together with its stronger influence on radical evolution, as reflected by the more pronounced reduction in key radical concentrations. To compare the suppression behaviours of N₂ and CO₂ under different conditions, three indices—the experimental maximum explosion overpressure suppression efficiency (S_T), the theoretical maximum explosion overpressure suppression efficiency (S_E), and the operating-condition suppression efficiency (η)—were introduced as comparative parameters. These results provide useful insight into the different suppression behaviours of N₂ and CO₂ in NH₃/H₂/air explosions. Full article

Although austenitic steels have been implemented in direct liquid hydrogen (LH₂) contact for decades, detailed microstructural and mechanical studies are still rare at a temperature of 20 K and inexistent for long-term exposure in LH₂. Therefore, austenitic stainless-steel parts, which were in direct contact with LH₂, from a container for LH₂ transport from the company Linde GmbH that has been in service for over 30 years, was chosen as a material model system for this investigation. In the present work, the possible influence of cryogenic gaseous and liquid H₂ (GH₂ and LH₂) on the micro- and macroscopic as well as mechanical properties of the container was investigated. Monitoring the properties after long-term GH₂ and LH₂-exposed material assesses the durability and the failure characteristics of these austenitic steels. A mean content of 2.5 ppm H was detected in the container walls after the long-term exposure. The microhardness of the long-term GH₂ and LH₂ are similar to an H₂ non-exposed sample. Based on the SEM investigations, no microstructural change could be detected in the material after long-term H₂ exposure and the residual tensile properties are still similar to those of ‘fresh’ non-exposed material. The hydrogen embrittlement (HE) occurred in the container material only after additional thermal H-charging, where the ductility reduced to about 50% at 200 K. Full article

This study explores a photovoltaic/thermal (PV/T)-based electrolysis system designed for dual production of hydrogen fuel and domestic hot water (DHW), providing a sustainable energy solution amid rising global emissions. A dynamic rule-based control mechanism with hysteresis thresholds on hydrogen-storage state of charge (SoC) is implemented to balance electrolyzer operation with intermittent solar availability, maintaining PV/T power outputs while preventing storage overfilling and minimizing start–stop cycling. The system is assessed across 27 geographically diverse cities spanning a wide range of solar irradiation and energy price structures. Annual hydrogen yields range from 20 kg/yr in high-latitude locations (Helsinki, Stockholm) to 33.5 kg/yr in high-irradiation regions (Riyadh, Abu Dhabi), while the levelized cost of hydrogen (LCOH) spans from 6.47 USD/kg (Riyadh) to 22.86 USD/kg (Helsinki). Economically, the system achieves its strongest performance in solar-rich, high-energy-cost environments: Rome records the highest net annual cash flow (858.9 USD/yr) and shortest payback period (2.47 years), followed by Davos, Madrid, Brasília, and Canberra. In contrast, locations with subsidized energy tariffs—such as Algiers, Kyiv, and Tehran—yield low or negative net cash flows, rendering the system economically unviable without policy support. Environmental analysis reveals annual CO₂ avoidance ranging from 0.33 ton/yr (Stockholm) to 2.97 ton/yr (Riyadh), with a global mean of 1.095 ton/yr and a combined total of approximately 29.6 tons/yr across all examined sites. A machine learning model is developed to generalize performance predictions across unseen locations, achieving leave-one-out (LOO) R² values of 0.953 (net cash flow), 0.935 (LCOH), and 0.947 (LCO-DHW), with mean absolute errors below ±1 USD/kg and ±0.03 USD/kWh. The findings confirm that, under fixed capital cost assumptions, local electricity price and solar irradiation are the dominant drivers of economic viability, while grid carbon intensity and solar resource jointly govern environmental performance, with markets offering irradiation above 1500 kWh/m²·yr and electricity prices exceeding 0.2 USD/kWh representing the most promising deployment targets. Full article