Search Results (4,343)

To address transportation-related emissions, Taiwan’s 2022 net-zero strategy sets targets to increase the adoption of battery electric vehicles (BEVs). However, current policy frameworks insufficiently consider the technological diversity of low-emission alternatives, particularly hydrogen fuel cell electric vehicles (FCEVs). This study integrates a well-to-wheel life cycle assessment (LCA) with system dynamics modeling to evaluate and compare the environmental and health impacts of transitioning from internal combustion engine vehicles (ICEVs) to BEVs and hydrogen FCEVs. The framework incorporates LCA-based carbon emissions and disability-adjusted life years (DALYs) into a dynamic population simulation. Results show that, while DALY effects on life expectancy and population growth are limited, low-carbon vehicle adoption substantially reduces environmental burdens and helps moderate population decline. Projections to 2050 highlight significant emission-reduction potential, with hydrogen FCEV carbon emissions decreasing as renewable energy in hydrogen production increases. Adoption of green hydrogen could achieve a net-negative carbon balance for hydrogen FCEVs by 2049, positioning them as a sustainable long-term alternative to BEVs. Full article

The shift from fossil fuels to renewable energy is a key component in achieving global sustainability and dealing with climate change. Natural resources, such as sunlight, air, water, and biomass, have tremendous potential to create clean energy; however, exploiting these resources in an efficient, stable, and large-scale integration manner is difficult due to their variable and distributed nature. Artificial intelligence (AI) approaches that mimic human learning and decision-making have recently become viable approaches to solving renewable energy problems. This study mainly examines the current landscape of AI applications across solar, wind, hydro, geothermal, ocean, hydrogen, bioenergy, and hybrid energy systems. AI enhances renewable energy forecasting, improves power system frequency analysis and stability assessments, and optimizes dispatch and distribution networks. Beyond technical optimization, AI also contributes to broader sustainability goals, including energy efficiency improvements, intelligent smart grid management, and enabling mechanisms such as carbon trading and circular economy practices to reduce exposure to climate extremes. Drawing on evidence from a range of renewable energy areas, this review highlights the importance of AI in bridging the link between technological innovation and sustainable energy management. This paper discusses potential future research avenues, such as building sophisticated AI designs, energy-efficient chips, and data communication networks. Ultimately, the synergy between AI and renewable energy systems represents not only a technological advancement but also a transformative pathway toward a resilient, low-carbon future. Full article

The rational configuration of electronic band structures through deep-seated structural disorder remains a formidable challenge in sustainable solar-to-fuel conversion. Herein, we report a transformative kinetic strategy to “freeze” an extraordinary density of non-equilibrium structural defects within an integrated Cu₄MgO₅/ZnO nanocomposite. Synthesized via a chitosan-assisted coordination-combustion route followed by rapid thermal quenching, the material preserves a record crystallographic dislocation density of 1.09 × 1015 m⁻² and significant lattice microstrain (1.04 × 10⁻³). This engineered structural disorder induces a profound reconfiguration of the electronic landscape, generating a continuous manifold of sub-bandgap “tail states” that narrow the optical bandgap to a remarkable 1.34 eV. Consequently, the defect-rich architecture facilitates unprecedented dual-channel photocatalytic performance under simulated solar irradiation in an aqueous solution containing 5 vol% triethanolamine (TEOA) as a sacrificial electron donor; the catalyst achieved a hydrogen evolution rate of 17,700.0 µmol g⁻¹ h⁻¹ and a methane production rate of 172.50 µmol g⁻¹ h⁻¹—representing a 36.3-fold and 43.1-fold enhancement over commercial ZnO, respectively. With an apparent quantum yield of 8.42% at 420 nm and robust photostability—maintaining 95.3% of its activity over five consecutive cycles (25 h total)—this noble-metal-free ternary system bypasses the limitations of traditional heterojunctions. Our findings establish a new benchmark for defect-engineered catalysts, providing a scalable blueprint for high-efficiency carbon neutrality and solar fuel production. Full article

Lamellar structure Ni-P catalysts were prepared on copper by the electrochemical deposition method for the hydrolysis of NaBH₄ solution. Voltage, time and temperature are key variables in the electroplating process, affecting the corrosion performance of the catalyst. The results show that as the deposition voltage (4–7 V) increases, the corrosion resistance of Ni-P at first is enhanced and then decreases, peaking at 5 V due to a more complete structure. Electroplating time and temperature affect the deposition of the nickel-phosphorus catalyst and then the corrosion resistance of the catalyst. Prolonged time and elevated temperature cause holes and cracks, degrading corrosion resistance. Therefore, a mild electroplating environment is preferred. The optimal electroplating temperature and time are 30 °C and 3 min, respectively. The polarization curve test shows that the Ni-P catalyst is greatly influenced by seawater temperature and chloride ion concentration in the actual service process, that the chloride ion is the dominant factor, and that the corrosion rate increases exponentially. Moreover, Ni-P/Cu catalysts mainly undergo localized corrosion and dissolution. Combined with Scanning Electron Microscope (SEM) and Energy Dispersive Spectrometer (EDS) analyses, the corrosion mechanism in seawater was systematically discussed. Full article

As the core pillar of international trade, the global shipping industry has seen its carbon and pollutant emissions become a key challenge in global environmental governance. Statistics indicate that ship carbon emissions account for 3% of the world’s total anthropogenic CO₂ emissions, while contributing 20% of global NO_x and 12% of SO₂ emissions, posing a serious threat to coastal ecosystems and public health. In response to the International Maritime Organization (IMO) “Net Zero Framework” and national green shipping policies, the transformation of ship power systems toward low-carbon and zero-carbon operation has become an inevitable trend. This paper systematically reviews the research progress and application status of green energy materials for ships, focusing on the working principles, technical characteristics, and engineering application cases of solar photovoltaic (PV) materials, wind energy utilization technologies, fuel cell materials, and alternative clean energy fuels (e.g., liquefied natural gas (LNG), methanol, and hydrogen energy). It also discusses the integration mode and optimization strategy of multi-energy hybrid power systems. The research findings show that solar photovoltaic technology has achieved large-scale application in coastal ships; hydrogen fuel cells are suitable for long-range ocean navigation scenarios due to their high energy density; LNG and methanol have become the current mainstream alternative fuels, relying on mature infrastructure; and hybrid energy systems can significantly improve power supply reliability and emission reduction efficiency through multi-energy complementarity. Finally, aiming at the existing bottlenecks (e.g., cost, energy storage, and safety) of various technologies, future development directions are proposed. This study provides a reference for the technological breakthrough and engineering practice of green energy power systems for ships and contributes to the realization of the “carbon neutrality” goal in the global shipping industry. Full article

Road freight contributes over half of China’s transport carbon emissions, making its decarbonization critical for carbon neutrality. This study combines total cost of ownership (TCO) and life cycle assessment (LCA) to analyze the economic efficiency and carbon emission effects of diesel, electric, and hydrogen fuel cell trucks. Combined with the LSTM neural network and vehicle ownership model, this study predicts the fleet emission reduction potential from 2020 to 2050. The results show that all new energy trucks can achieve TCO parity with diesel trucks before 2050, and electrification shows better economic competitiveness than hydrogen fuel cell technology across all vehicle types in the Chinese context. Fuel cell trucks powered via solar-powered water electrolysis exhibit the lowest carbon intensity, and grid decarbonization can significantly improve the emission reduction effects of electric and fuel cell trucks. Freight fleet carbon emissions are expected to peak around 2030. In an ideal scenario, emission reductions of 19.5%, 41.9%, and 82.9% can be achieved by 2030, 2040, and 2050, respectively. Heavy-duty trucks are the main emission contributors (47–58%) and the main target of emission reduction strategies. Short-term reduction depends on fuel economy, while long-term reduction prioritizes new energy substitution. Policy recommendations include promoting alternative fuel trucks, upgrading emission standards, and adopting differential taxation. Full article

The emission of hydrogen cyanide (HCN) from formaldehyde (CH₂O) during ammonia-assisted selective catalytic reduction (NH₃-SCR) remains a critical challenge for aftertreatment of bio-hybrid fuel combustion exhaust. The mechanistic details of HCN formation are still poorly understood, especially on widely deployed commercial catalysts like Cu-SSZ-13. In this work, we employed density functional theory calculations in combination with the Energetic Span Model to elucidate HCN formation pathways from CH₂O in the presence of NO₂ and H₂O over Cu-SSZ-13. The results revealed the HCN formation pathway with intermediate methylene imine as the dominant one under typical reaction conditions. These findings resonate very well with reports of hexamethylenetetramine (HMT) formation during NH₃-SCR with CH₂O, for which methylene imine is a critical intermediate. Turnover frequency (TOF) estimations highlighted the strong influence of NO₂ and H₂O: higher NO₂ concentrations promoted CO selectivity and suppressed HCN by oxidizing CH₂O to HCOOH, while lower H₂O enhanced HCN formation. These findings establish a detailed mechanistic framework for HCN emission on Cu-SSZ-13 and suggest that controlling NO₂/NO_x ratios and water content can mitigate HCN formation during NH₃-SCR. Full article

Road freight transport is an important driver of global greenhouse gas (GHG) emissions. Decarbonizing this sector demands a comprehensive assessment of emerging powertrain technologies, which are currently lacking in the literature. To fill this knowledge gap, we performed a life cycle assessment (LCA) on 10 impact categories to evaluate road freight transport in the Netherlands of four truck alternatives, assuming similar performance: fuel-cell electric (FCEV), hydrogen internal combustion engine (HICEV), battery electric (BEV), and diesel internal combustion engine (DICEV). We compared locally produced green hydrogen, according to EU regulations, with electricity and diesel as alternative fuel chains, while also considering the environmental impact of road infrastructure. We found that FCEV and HICEV trucks achieve the lowest global warming impact when green hydrogen is used. We identified discrepancies between the transport alternatives, highlighting key factors influencing NO_x and particulate matter emissions. Our research also showed that water consumption (WC) for green hydrogen is strongly influenced by upstream processes, with solar-powered electricity emerging as a crucial contributor. Our results highlight the need for more exploration on the environmental impact of green hydrogen and can be used by researchers and practitioners to further understand the complexity of reducing emissions in road freight transport. Full article

Given the large natural gas (NG) reserves of the Intermountain West (I-WEST) region in the USA, it can emerge as a leader in hydrogen (H₂) production. Currently, H₂ production via steam methane reforming (SMR) of NG releases carbon dioxide (CO₂) and the natural gas infrastructure has fugitive NG and H₂ losses during production, conversion and transportation. Integrated carbon capture and sequestration (CCS) is a promising approach for producing hydrogen and CO₂ from the SMR process for industrial uses including power, chemicals and fuels. However, the NG losses and regional water availability can be limiting factors for H₂ production. H₂ production assessments are often made at the global scale and neglect regional factors such as abundant gas and limited water in the I-WEST. We demonstrate that a regional SMR process unit sitting near NG wells offers opportunities to significantly reduce fugitive NG losses. We show that regional H₂ production by SMR has a lower emissions profile than widespread natural gas combustion in the I-WEST and reduces the H₂ production cost as well. Replacing the I-WEST transportation sector with H₂ fuel cell vehicles and using 100% H₂-powered electricity can provide substantial reductions in water consumption and fuel costs. This is better than blending H₂ with NG which is more expensive. The captured CO₂ can be effectively used for enhanced oil recovery in I-WEST. Finally, the potential of utilizing produced, brackish and treated impaired water sources is assessed to meet the water needs for H₂ production in the I-WEST. Full article

In this study, density functional theory (DFT)-based investigations are carried out using the CASTEP code. The plane-wave pseudopotential method is used to explore the multifunctional properties, including the structural, electronic spectra, thermo-mechanical and hydrogen storage properties, of hydrogen-rich mixed-anionic (Li₃H₄N₂X, where X = F, Cl, Br, and I) halides. The exchange–correlation interactions are treated within the generalized gradient approximation (GGA) using the Perdew–Burke–Ernzerhof (PBE) functional, while the hybrid HSE06 function is used for accurate band gap predictions. Moreover, the optical properties of the halides are analyzed under the influence of UV–Vis radiation instances. The band gap values of these orthorhombic-structured halides lie in the visible-to-UV regions of radiation, with values of 2.97 eV, 3.12 eV, 3.06 eV and 3.28 eV, respectively. Such band gap values allow these materials to absorb nearly 75% to 90% of incoming radiation, with absorption values around (10⁵ cm⁻¹). These favorable opto-electronic responses make these halides suitable for solar radiation energy conversion applications. Stable thermodynamic responses and the mechanical nature of the mixes (brittle for Li₃H₄N₂Br and ductile for the rest) reveal their practical applicability for flexible photonics. Moreover, due to the presence of rich hydrogen atoms, the Li₃H₄N₂F halide exhibits a gravimetric ratio of around 6.0 wt%, which is higher than the standard (5.5 wt%) value defined by the US DOE. Similarly, GHSC values of 2.5 wt% for Li₃H₄N₂I, 3.5 wt% for Li₃H₄N₂Br, and 5.0 wt% for Li₃H₄N₂Cl are reported; these values indicate that these compounds possess strong potential for use in the hydrogen fuel cells required in light-duty vehicles. Full article

Hydrogen enrichment of compression ignition (CI) engines has emerged as a promising strategy to simultaneously enhance thermal efficiency and reduce carbon-based emissions. This study numerically investigates how hydrogen enrichment affects engine performance and emissions in methanol–diesel dual-fuel CI engines, a combustion mode gaining increasing attention for replacing fossil diesel with sustainable fuels, particularly in hard-to-abate sectors such as maritime transport. The simulations are based on the Unsteady Reynolds-Averaged Navier–Stokes (URANS) equations, incorporating the RNG k-ε turbulence model, the Eddy Dissipation Concept (EDC) for turbulence–chemistry interaction, and the G-equation for turbulent premixed flame propagation. The numerical model is validated against experimental data for in-cylinder pressure and heat release rate at 45% methanol substitution ratio (by energy). The results indicate that increasing the hydrogen enrichment ratio (HER, defined on an energy basis) from 5% to 20% raises the Sauter mean diameter (SMD) of the diesel fuel from 20.2 µm to 28.0 µm (+38%), driven by reduced aerodynamic breakup intensity associated with modified gas-phase properties under hydrogen enrichment. Furthermore, hydrogen’s elevated adiabatic flame temperature and superior mass diffusivity intensify combustion, raising peak in-cylinder pressure from 75.2 to 79.1 bar (+5.2%), amplifying the peak heat release rate from 129 to 211 J/°CA (+63.6%), and elevating maximum in-cylinder temperature from 1542 to 1735 K (+193 K). Under the investigated CFD operating conditions, these thermodynamic gains translate into an engine-level 6% improvement in indicated thermal efficiency and a 14% reduction in indicated specific fuel consumption (accounting for hydrogen, methanol, and diesel) at HER 20%. On the emissions front, CO₂ declines by 24% in direct proportion to the carbon-containing fuel mass displaced by hydrogen substitution, while NO_x increases approximately twofold from 0.10 g/kWh at HER 0 to 0.21 g/kWh at HER 20, driven by peak temperature elevation. These findings establish hydrogen-enriched methanol–diesel dual-fuel combustion as a viable pathway toward high-efficiency, low-carbon CI engine operation for heavy-duty transport applications. Full article

Direct Coal Liquefaction (DCL) is a promising route for converting abundant coal resources into liquid fuels, yet its efficiency remains strongly dependent on catalyst performance. In this work, we present an integrated computational framework combining density functional theory (DFT) calculations with machine learning (ML) to investigate iron–sulfur (FeS) cluster catalysts for DCL. DFT calculations were employed to examine hydrogen-donor dissociation and coal-derived radical hydrogenation on representative FeS clusters. The results indicate that the most favorable catalytic pathways arise from the cooperation between metallic Fe sites (Fe_2) and interfacial Fe sites adjacent to sulfur (Fe_1), while sulfur atoms mainly play an indirect structural and electronic modulation role. Based on these mechanistic insights, a database containing thermodynamic and kinetic data for 636 reactions across 50 FeS cluster models was constructed. This dataset was then used to train three ML classifiers, among which the Random Forest model showed the best performance, reaching accuracies of 80% for H-donor cleavage and 93% for radical hydrogenation on the held-out test sets. SHapley Additive exPlanations (SHAP) analysis further showed that descriptors associated with Fe active-site identity were among the most influential variables in both tasks. Overall, this work provides a mechanistically informed and interpretable computational framework for understanding FeS-catalyzed DCL chemistry and for the preliminary screening of catalyst motifs within the chemical space covered by the present FeS cluster library. Full article

To accelerate the transition to sustainable energy, efficient methods for CO₂-free hydrogen production and carbon utilization are needed. This study presents a new, sustainable approach for the simultaneous production of hydrogen, valuable hydrocarbons, and functional carbon materials by converting methane in low-pressure microwave plasma. Compared to traditional methane reforming methods (such as steam reforming), our plasma-based process operates at low temperatures, eliminates direct CO₂ emissions, and enables the conversion of methane into three valuable products: (1) environmentally friendly hydrogen for fuel cells and energy storage systems, (2) a range of valuable organic products (C₂H₂, C₂H₄, C₂H₆), and (3) functional carbon films with self-improving catalytic properties. Optical emission spectroscopy (OES) and the Langmuir double probe method were used for plasma diagnostics, revealing an increase in the concentration of active species (CH, Hα, C₂) and electron temperature upon argon addition. The structure, morphology, and impurity composition of the deposited films were investigated using X-ray diffraction (XRD), scanning electron microscopy (SEM), and inductively coupled plasma mass spectrometry (ICP-MS), respectively. Gas-phase byproducts were analyzed using gas chromatography–mass spectrometry (GC-MS). Argon addition at an Ar/CH₄ ratio of 1 leads to the formation of carbon films with a more ordered structure, as confirmed by XRD data, and improved surface morphology. It was established that argon, by effectively participating in the excitation and dissociation processes of methane molecules through energy transfer from metastable states and increased electron temperature, optimizes plasma–chemical reactions, promoting the deposition of higher-quality carbon coatings. Full article

The increasing adoption of alternative fuels such as hydrogen and ammonia in energy systems has created a growing need for advanced diagnostic techniques capable of monitoring combustion products with high specificity and flexibility. In this context, Raman spectroscopy represents a promising optical approach for gas analysis, as it enables the simultaneous detection of multiple species without requiring sample preparation. In this work, the performance of a cost-effective Raman-based system on quantitative detection of nitrogen oxides (NO and NO₂) and nitrous oxide (N₂O) is presented. The experimental setup is based on a multi-pass optical configuration designed to enhance the Raman signal and employs off-the-shelf components, including an uncooled CMOS detector. Calibration measurements were carried out using gas mixtures at known partial pressures, and gas concentrations were retrieved through a nonlinear least-squares fitting procedure applied to the measured spectra. The results show that the system provides linear and repeatable responses for NO and N₂O over the investigated pressure ranges, with low mean errors and limited data dispersion, while NO₂ performance could not be fully quantified in a comparable manner due to the high reactivity of the species under the tested conditions. Overall, the proposed system represents a viable and cost-effective solution for multi-species gas analysis in emerging combustion applications. This work aims to extend the industrial applicability of Raman spectroscopy to NO_x and NO₂ diagnostics. Full article

Agriculture plays a relevant role in the food supply chain but is also a major contributor in terms of emissions. A possible solution to reduce its impact is to replace traditional machinery with innovative systems, such as agricultural rovers. In the proposed research, a case study of an agricultural rover, specifically designed to operate in orchards, is presented. The powertrain features a Li-ion battery pack as the primary energy source and a fuel cell system operating as a range extender unit. Hydrogen is stored on board using a metal hydride tank to enhance compactness. Once the traction and range extender power output control strategies were defined, experimental tests in a closed warehouse were performed. During the tests, the rover was manually controlled using a joystick, since the main focus was to evaluate the powertrain behavior rather than to test the autonomous driving algorithm. During the tests, different maneuvers in narrow spaces were performed. The results showed that the rover successfully accomplished the tasks and the range extender unit can effectively extend the rover autonomy up to +150% compared to the pure battery solution. This result was obtained considering a 15 min test carried out in an indoor environment with a polished concrete floor. Full article