Search Results (310)

Nanostructured catalysts have become a core component of energy conversion in electrocatalysis and photocatalysis; however, successfully translating their performance from laboratory scale to industrial applications remains a long-standing challenge. This paper provides a critical assessment of the field, systematically tracing the entire development trajectory from catalyst design to practical application. We focus on five major classes of catalysts—monometallic catalysts, bimetallic/multimetallic alloy catalysts, metal compound catalysts, carbon-based composite catalysts, and single-atom catalysts—and explore synthetic strategies for achieving precise structural control, including hydrothermal/solvothermal methods, electrodeposition, template-assisted and MOF-derived syntheses, high-temperature pyrolysis, and post-treatment defect engineering. This paper delves into the mechanisms and performance descriptors governing the hydrogen evolution reaction (HER), oxygen evolution reaction (OER), oxygen reduction reaction (ORR), urea oxidation, photocatalytic water splitting, and CO₂ reduction. Based on the above analysis, this paper lays the mechanistic foundation for five core strategies to improve catalyst performance: morphology control, elemental doping, heterostructure and interface engineering, defect and vacancy engineering, and support modification. Furthermore, this paper provides an in-depth evaluation of the applications of these catalysts in water splitting, CO₂ valorization, fuel cells, metal–air batteries, and energy-saving electrolysis, with a particular focus on earth-abundant alternatives to precious metals. We argue that in many well-studied reactions, intrinsic activity may no longer be the primary bottleneck restricting their development; instead, the core challenge now lies in maintaining excellent catalytic performance under harsh and industrially relevant conditions, especially under high-current densities, impurity-containing feed systems, and long-term operating conditions. In response to this shift in research focus, this paper clearly identifies the key obstacles hindering the industrial application of catalysts and proposes practical directions for future research. Full article

In order to optimize the sealing structure of the electrolytic cell for hydrogen production by electrolysis of water and enhance its sealing performance, a finite element model of the electrolytic cell sealing was established using software. The influence of different parameters of the sealing rib structure on the sealing performance was studied, and the variation law of gasket compressive stress under different sealing rib slot widths, angles, and spacings was explored. The results show that under the material constants of C10 = 7.0 × 10⁻³ and C01 = 6.05 in the Mooney–Rivlin constitutive model of the gasket, the gasket will deform and embed into the sealing rib groove after compression. At the same time, two parts of stress concentration will occur at the contact area between the gasket and the sealing rib groove, namely tensile stress concentration and compressive stress concentration. This stress concentration is the main source of sealing effect in practical work. After adding the sealing rib groove, the contact area between the sealing rib area and the gasket increases. When maximizing the peak sealing compressive stress serves as the optimization criterion, the optimal pitch settles at 0.4 mm; if the optimization objective shifts to attaining the utmost contact area, the preferable spacing amounts to 1 mm, accompanied by a maximum contact area increment of 34.31 percent. After comprehensive deliberation over sealing stress magnitude, functional sealing area, gas tightness efficiency as well as practical engineering applicability, 0.8 mm is pinpointed in this dissertation as the globally optimal spacing dimension. With a sealing rib pitch of 0.8 mm, a breadth of 1 mm, and an inclined angle of 20 degrees, the gasket yields substantial sealing stress alongside optimized post-assembly sealing contact area, wherein 26.44 percent of the overall gasket area contributes to effective sealing performance. Full article

The increasing worldwide demand for sustainable energy and effective waste management has heightened interest in solutions. Microbial fuel cells (MFCs) represent a potential category of bioelectrochemical systems that directly transform the chemical energy contained in organic waste into electrical energy via the metabolic processes of electroactive microorganisms. In the last twenty years, significant advancements have occurred in the comprehension of extracellular electron transfer (EET) mechanisms, biofilm formation, microbial community dynamics, electrode material engineering, and reactor design, resulting in marked enhancements in power density and wastewater treatment efficacy. Despite these breakthroughs, the extensive deployment and commercialization of MFC technology are constrained by various hurdles, including inadequate energy recovery, elevated material and fabrication expenses, operational instability, and the intricacies of system scale-up. This cutting-edge analysis offers a thorough evaluation of recent advancements in MFCs and their incorporation with sophisticated technology for waste management and energy generation. Focus is directed towards essential bioelectrochemical principles, microbial and biofilm engineering techniques, sophisticated electrode and membrane materials, reactor designs, and hybrid MFC systems integrated with anaerobic digestion, microbial electrolysis, and advanced oxidation methods. Ultimately, emerging trends, significant knowledge deficiencies, and future research goals are defined to inform the advancement of next-generation MFC systems that support circular economy and net-zero energy initiatives. Full article

This paper assesses the role of green hydrogen and green ammonia in the low-carbon reconstruction of Ukraine’s energy sector. The country, severely affected by war, has more than 70% of its energy infrastructure damaged or destroyed, which calls for novel solutions for not only reconstructing but also rethinking Ukraine’s energy sector shaped by the Soviet-era planning. In this context, decentralized and renewable energy solutions appear to be one of the best options to achieve this goal. This study combines four novel and mutually reinforcing methods: a Scopus-based literature review of highly cited green hydrogen publications, natural language processing (NLP) and bibliometric network analysis of Ukraine-related hydrogen research, a SWOT assessment, and a geospatial hydrogen production cost model (GEOH2). The novelty of this research lies in this integrated Ukraine-specific framework, which links research trends, wartime reconstruction constraints, hub-level policy choices, and financing risk-sensitive cost modeling. Therefore, the quantitative part of GEOH2 estimates the levelized cost of green hydrogen, while ammonia is treated as a downstream screening-level conversion and export pathway rather than as a full plant-level ammonia model. Our results show that Ukrainian green hydrogen research is concentrated on renewable-energy strategy, wind and solar electrolysis, water and desalination constraints, gas grid blending, underground storage, ammonia derivatives, and decentralized energy systems. The GEOH2 results indicate that southern Ukraine has strong physical potential for competitive green hydrogen production under de-risked financing, while war risk financing can make even resource-rich areas economically unattractive. Odesa and Dnipro emerge as important export-oriented and industrial hubs, whereas Zakarpattia remains strategically relevant as a safer western corridor linked to European markets. Our findings demonstrate that Ukraine’s hydrogen and ammonia development needs to follow a phased pathway: domestic renewable build-out and grid repair, pilot electrolysis projects and screening-level ammonia conversion pathways, targeted de-risking and insurance mechanisms, and only then broader export corridor development. This pathway can support decarbonization, energy security, industrial modernization, and Ukraine’s long-term integration into European clean energy value chains. Full article

Adiponitrile (ADN) serves as a critical intermediate for manufacturing polyamide 66. Electrochemical hydrodimerization of acrylonitrile (AN) offers a green and sustainable route for ADN production, yet conventional lead plate cathodes still suffer from high cell voltage, insufficient mechanical stability, and lead dust shedding during long-term operation. In this work, we developed a novel composite lead electrode in ambient air to overcome these drawbacks. Key preparation parameters, including calcination temperature, polytetrafluoroethylene (PTFE) content, substrate type, dispersion method, and dispersant dosage, were carefully screened and optimized. The optimal conditions were determined as follows: PTFE mesh as the substrate, 10% PTFE relative to lead powder, mechanical stirring dispersion, 0.5 wt% sodium hexametaphosphate as dispersant, air calcination at 325 °C, and subsequent electrochemical reduction. SEM, XRD, and XPS characterizations showed that the optimized electrode features a three-dimensional porous network assembled from interlaced rod-like and flower-like micro/nanostructures, which greatly elevates the specific surface area, enriches active sites, and facilitates electrolyte penetration and mass transport. After electrochemical reduction, the electrode surface was dominated by catalytically active Pb⁰. Electrochemical tests indicated that the composite electrode delivered a current density of 60–70 mA·cm⁻² at −1.6 to −2.0 V (vs. SCE) for AN reduction, nearly three times higher than that of a conventional lead plate. In addition, the composite electrode showed improved mechanical hardness and completely suppressed lead dust shedding, greatly enhancing operational safety and service life. Stable voltage was maintained during long-term electrolysis. This study provides a low-cost and scalable strategy for fabricating high-performance lead-based composite cathodes, which can support the industrial-scale green electrosynthesis of adiponitrile from acrylonitrile. Full article

This study evaluated the degradation of 1,3,5,7-tetranitro-1,3,5,7-tetrazocane (HMX) in simulated wastewater using an iron-carbon (Fe-C) micro-electrolysis system. The treatment efficiency was systematically evaluated under varying initial pH, Fe dosage, and Fe/C mass ratios. Under the optimized operating conditions (initial pH of 4, Fe dosage of 70 g/L, and an Fe/C mass rat of 1:1), the system achieved a maximum HMX removal efficiency of 98.4%. Kinetic analysis indicated that the degradation process conformed to pseudo-first-order kinetics. Mechanistically, HMX removal was attributed to interfacial adsorption and co-precipitation via in situ generated Fe²⁺ and Fe³⁺ hydroxides, alongside reductive transformation mediated by Fe, Fe²⁺, and nascent hydrogen ([H]) evolved during the micro-electrolysis process. To assess the molecular toxicity evolution of the treated wastewater, a toxicogenomic assay was deployed to evaluate the molecular toxicity evolution of the treated wastewater matrix. The transcriptomic profiling revealed that DNA damage and oxidative stress were the predominant cellular stress responses induced by the wastewater. While the total toxic effect transcript index (TELI_total) exhibited a transient initial increase before steadily declining, the overall toxic potency remained within a relatively stable range throughout the treatment cycle. Ultimately, this study provides critical insights into process optimization and pathway elucidation, demonstrating that Fe-C micro-electrolysis is a promising and scalable pretreatment technology for the remediation of energetic compound-laden industrial effluents. Full article

Electrochemical water splitting stands as a feasible approach for sustainable hydrogen production, but its industrial implementation is restricted by sluggish oxygen evolution reaction (OER) kinetics and excessive dependence on freshwater resources. As a widely existing alternative, seawater contains a high concentration of chloride ions (Cl⁻), which give rise to serious electrode corrosion and catalyst deactivation, bringing great challenges to actual electrolysis applications. Herein, we report a facile room-temperature two-step soaking strategy to fabricate sulfur-modified NiFe layered double hydroxide (S-NiFe-LDH) catalysts for efficient OER in both alkaline freshwater and seawater electrolytes. The introduction of sulfur not only optimizes the electronic structure of NiFe-LDH to strengthen intrinsic catalytic activity and speed up charge transfer, but also promotes the formation of a Cl⁻-resistant layer, thus significantly improving corrosion resistance. In addition, DFT calculations show sulfur modification in NiFe layered double hydroxide upshifts the O 2p-band center to activate lattice oxygen, switches the oxygen evolution reaction pathway to the lattice oxygen mechanism with reduced thermodynamic barriers, and realizes the selective adsorption of OH⁻ over Cl⁻. As a result, the as-prepared S-NiFe-LDH catalyst exhibits exceptional OER performance, requiring overpotentials (η) of 250, 270, and 290 mV to reach current densities of 50, 100, and 200 mA·cm⁻² in 1 M KOH, respectively, with a Tafel slope of 22.3 mV·dec⁻¹. Moreover, it maintains remarkable stability for more than 200 h in alkaline seawater electrolytes and achieves nearly 100% Faradaic efficiency for water splitting, effectively avoiding the parasitic chlorine evolution reaction (CER). This work provides a scalable and energy-efficient synthetic route for designing advanced non-noble metal catalysts, paving the way for industrial-scale hydrogen production from seawater. Full article

Hydrogen energy, as an important green energy source, is a crucial guarantee for achieving carbon neutrality and peak carbon emission. The anion exchange membrane (AEM) electrolysis cell combines the advantages of alkaline electrolysis cell and proton exchange membrane electrolysis cell and can employ non-precious metal catalysts combined with renewable energy, which is expected to break through the bottleneck of high production cost of green hydrogen. AEM water electrolysis combines the advantages of alkaline and proton exchange membrane water electrolysis for hydrogen production. It has the characteristics of high electrolysis efficiency, fast response rates, and low cost, and its considered one of the most promising renewable green energy hydrogen production technologies at present. AEM is a key component that provides OH^– ion conduction and blocks gas crossover, which directly affects the performance and service life of the AEM electrolysis water system. However, current AEMs face issues of low ion conductivity and poor stability. This review introduces the role of AEM in electrolytic cells, the performance requirements and evaluation parameters that high-performance AEM should meet, and focuses on the transport mechanism and influencing factors of OH^– in AEM. Furthermore, this review provides an overview of the structural composition of AEM, as well as common cationic groups and polymer backbone types. The degradation mechanism of various cationic groups and the characteristics of polymer main chains were elaborated, with a focus on the strategies for designing the stability of cationic functional groups, the methods for modifying and preparing polymer main chains, and the performance of AEMs. Finally, the future challenges and potential research directions of AEM membranes are discussed. It is suggested that high-performance AEMs meeting practical application needs should be developed through strategies such as crosslinking, block copolymerization, side chain grafting, and composite membrane technology, based on the design of alkali-resistant and stable AEM membranes. These insights provide reference and guidance for the further development of AEMs. Full article

The main challenge of hydrogen electrolysis lies in the high cost of hydrogen production. Achieving a decarbonized energy sector requires substantial investment to shift from carbon-intensive technologies to more sustainable alternatives. However, investment decisions in this context remain complex and uncertain. Currently, green hydrogen projects account for more than 500 initiatives worldwide and are expected to expand rapidly in the coming years. Evidence from feasibility studies suggests that green hydrogen produced from renewable energy is already technically viable and is approaching economic competitiveness. The current emphasis is on large-scale deployment and learning-by-doing processes to reduce electrolyzer costs and improve supply chain efficiency. This transition requires appropriate funding mechanisms, often involving significant public sector participation alongside private investment. This study analyzes the financing structures of green hydrogen projects in Germany, Australia, and Brazil using Principal Component Analysis (PCA) to identify the most relevant combinations of technical, economic, and financial variables. Unlike previous studies that address technical, economic, and financial dimensions in isolation, this study offers an integrated, empirically grounded analysis at the project level, combining cross-country comparison with a multivariate approach. The results indicate that project characteristics are strongly associated with capital intensity and financing structures, while cost variables such as levelized cost of hydrogen (LCOH) play a secondary role in explaining variation across projects. These findings suggest that financing arrangements—particularly those involving public support mechanisms—are closely associated with project configuration in this emerging sector. However, these results should be interpreted as patterns of statistical association rather than evidence of causal relationships. Overall, the analysis highlights the importance of coordinated financing strategies in supporting the development of green hydrogen and its potential contribution to emissions reduction in line with the Paris Agreement and the transition toward climate neutrality. Full article

Proton exchange membrane water electrolysis is a promising technology for large-scale green hydrogen production due to its high efficiency, compact design, and rapid dynamic response. However, its commercialization is strictly limited by high material costs, durability issues, and complex multiphysics coupling within the membrane electrode assembly. This work provides a comprehensive and critical review of key physicochemical processes and advanced predictive modeling approaches for PEMWEs. To capture recent paradigm shifts, we introduce an innovative multi-dimensional classification framework—incorporating spatial resolution, temporal dynamics, and methodological paradigms—to critically evaluate lumped-parameter, continuum, microscale, and multiscale models, explicitly defining their applicability bounds and inherent limitations. The fundamental mechanisms governing electrode kinetics, membrane water transport, and gas–liquid two-phase flow are analyzed, establishing state-of-the-art quantitative benchmarks for microstructural parameters and advanced 3D flow field topologies under high-current-density and high-pressure regimes. Furthermore, we systematically examine model validation rigor, typical prediction errors, and the critical failure of static models in capturing dynamic property shifts during extreme bubble breakthrough. Recent breakthroughs integrating in situ diagnostics, pore-scale simulations, density functional theory, and Physics-Informed Neural Networks are extensively discussed. Future efforts must prioritize mechanical–electrochemical–thermal coupling, transient degradation prognostics, and machine learning-driven predictive digital twin technologies to overcome current empirical limitations and accelerate the gigawatt-scale deployment of PEMWE systems. Full article

The Agricultural Energy Internet (AEI) represents an emerging systemic paradigm driven by the convergence of intelligent agriculture and rural energy transformation. It is not a simple extension of agricultural informatization or rural electrification; rather, it redefines agricultural processes—such as irrigation, greenhouse environmental control, supplementary lighting, cold-chain logistics, and agricultural machinery—as perceptible, computable, and schedulable energy-related processes, thereby enabling the deep integration of agriculture, energy, environmental management, and intelligent decision-making. This review systematically examines the evolutionary trajectory of AEI, from early agricultural digitalization and Internet of Things (IoT)-based monitoring to edge intelligence and digital twin technologies, and ultimately to the coordinated optimization of agriculture–energy–environment systems. A comprehensive technical framework is established, encompassing physical energy coupling, multi-source sensing and actuation, interconnection and interoperability, edge–cloud collaborative control, data governance, digital twin modeling, artificial intelligence-enabled optimization, and application-oriented decision-making. The review further highlights that high-quality data governance, edge–cloud collaboration, and digital twin calibration are critical enablers of the transition from visualization-oriented management to closed-loop intelligent operation. In addition, this study clarifies the complementary relationship between agricultural informatization and electrification: the former provides capabilities for perception, prediction, optimization, and coordination, whereas the latter provides a controllable execution chain. Together, they constitute the foundation of a cyber-physical agricultural energy system. Finally, frontier research directions are identified, including high-temperature solid oxide electrolysis for hydrogen production, edge AI–IoT-enabled closed-loop agricultural operation, and privacy, security, and trust mechanisms in federated edge intelligence. The findings suggest that AEI can serve as a strategic technological framework for supporting the next generation of smart agriculture toward low-carbon, resilient, and collaborative operation. 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

In this study, first-principles molecular dynamics (FPMD) simulations were employed to systematically investigate the effects of temperature and composition on the microstructure and transport properties of CaCl₂–CaI₂ mixed molten salts at the atomic scale. Structural analysis shows that the system exhibits good relaxation behavior and thermodynamic stability, with coordination strength following Ca-Cl > Ca-I. The transport properties reveal a coupled dependence on temperature and composition: increasing CaI₂ content enhances the diffusion of I⁻ ions, whereas at 1173 K, a decrease in diffusion coefficients is observed for all ionic species. Arrhenius analysis indicates that increasing CaI₂ content lowers the activation energy for ion migration. The shear viscosity follows the order η(Ca²⁺) > η(Cl⁻) ≥ η(I⁻), and decreases with increasing temperature and CaI₂ concentration, indicating improved fluidity. Notably, the results reveal a competitive coordination mechanism between Cl⁻ and I⁻ around Ca²⁺, as well as a non-monotonic transport behavior at high temperatures, reflecting the complex coupling between composition and ionic dynamics in mixed halide melts. This study provides a theoretical basis for the optimization of molten salt electrolysis processes and nuclear energy materials, and offers insight for future multiscale simulations and experimental validation. Full article

The 316L stainless steel is widely utilized as structural material in hydrogen production industry due to its excellent combination of corrosion resistance and mechanical properties. However, it remains susceptible to localized pitting corrosion in chloride-containing high-temperature environments. Especially, the main electrolysis byproduct sodium chlorate (NaClO₃) also has complicated effect on pitting corrosion. Therefore, evaluating and predicting the pitting severity grades of 316L steel in NaClO₃ and NaCl environment is essential for controlling operation risks. In recent years, machine learning (ML) methods have gained significant attention in the field of corrosion prediction; however, existing research has primarily focused on the regression prediction of continuous parameters, while studies dedicated to the classification and evaluation of pitting severity grades remain relatively limited. Furthermore, experimental datasets are commonly constrained by small sample sizes and imbalanced class distributions, which hinder the performance enhancement of classification models. Based on experimental pitting data of 316L stainless steel, this study employs ADASYN (Adaptive Synthetic Sampling) to mitigate data imbalance and develops a Feedforward Neural Network (FFNN) for pitting rate classification. The proposed model is compared and analyzed against several commonly used machine learning models. Through a comprehensive evaluation of predictive performance, the feasibility of the developed model in pitting severity grading is verified, thereby providing a novel approach for the predictive evaluation of the pitting corrosion of 316L stainless steel. Full article

In the context of global carbon neutrality, photovoltaic (PV)-coupled water electrolysis has emerged as a pivotal technological route for large-scale green hydrogen production. This review systematically explores the integration of diverse PV technologies (e.g., crystalline silicon, perovskite tandems, and concentrated PV) with various electrolysis systems (such as AEL, PEMEL, and AEMEL). We analyze the coupling mechanisms across light–electricity–hydrogen multi-energy fields from three dimensions: PV spectral response matching, electrolyzer kinetic adaptation, and innovative system topologies. Furthermore, this paper highlights critical scientific challenges, including the mismatch between fluctuating PV output and steady-state electrolysis, lifecycle stability under extreme conditions, and the optimization of high-cost catalysts. By incorporating cutting-edge approaches like AI-driven predictions, digital twins, and photothermal synergies, we outline future trajectories for enhancing system efficiency and economic viability. Ultimately, this review provides theoretical guidance to advance the commercialization of diverse, stable, and low-cost PV-driven green hydrogen production systems. Full article