Search Results (960)

Hydrotreated ester and fatty acids to jet (HEFA-tJ) is presently the most developed and economically attractive pathway to produce sustainable aviation fuel (SAF). An ongoing systematic study of the critical variables of different pathways to SAF has revealed significantly lower greenhouse gas (GHG) reduction potential for the HEFA-tJ pathway compared to competing markets using the same resources for road diesel production. Moderate yield variations between air and road pathways lead to several hundred thousand tons less GHG reduction per project, which is generally not evaluated thoroughly in standard environmental assessments. This work demonstrates that, although the HEFA-tJ market seems to have more attractive features than biodiesel/renewable diesel, considerable viability risks might manifest as HEFA-tJ fuel market integration rises. The need for more transparent data and effort in this regard, before envisaging making decisions regarding the volume of HEFA-tJ production, is emphasized. Overall, reducing the carbon intensity of road diesel appears to be less capital-intensive, less risky, and several times more efficient in reducing GHG emissions. Full article

Industrial catalysts are accelerating the global transition toward renewable energy, serving as enablers for innovative technologies that enhance efficiency, lower costs, and improve environmental sustainability. This review explores the pivotal roles of industrial catalysts in hydrogen production, biofuel generation, and biomass conversion, highlighting their transformative impact on renewable energy systems. Precious-metal-based electrocatalysts such as ruthenium (Ru), iridium (Ir), and platinum (Pt) demonstrate high efficiency but face challenges due to their cost and stability. Alternatives like nickel-cobalt oxide (NiCo₂O₄) and Ti₃C₂ MXene materials show promise in addressing these limitations, enabling cost-effective and scalable hydrogen production. Additionally, nickel-based catalysts supported on alumina optimize SMR, reducing coke formation and improving efficiency. In biofuel production, heterogeneous catalysts play a crucial role in converting biomass into valuable fuels. Co-based bimetallic catalysts enhance hydrodeoxygenation (HDO) processes, improving the yield of biofuels like dimethylfuran (DMF) and γ-valerolactone (GVL). Innovative materials such as biochar, red mud, and metal–organic frameworks (MOFs) facilitate sustainable waste-to-fuel conversion and biodiesel production, offering environmental and economic benefits. Power-to-X technologies, which convert renewable electricity into chemical energy carriers like hydrogen and synthetic fuels, rely on advanced catalysts to improve reaction rates, selectivity, and energy efficiency. Innovations in non-precious metal catalysts, nanostructured materials, and defect-engineered catalysts provide solutions for sustainable energy systems. These advancements promise to enhance efficiency, reduce environmental footprints, and ensure the viability of renewable energy technologies. Full article

Biodiesel, as one of the alternatives to fossil fuels, faces significant challenges in large-scale industrial production due to its high production costs. In addition to raw material costs, catalyst costs are also a critical factor that cannot be overlooked. This review summarizes various methods for preparing biodiesel catalysts from solid waste. These methods not only enhance the utilization rate of waste but also reduce the production costs and environmental impact of biodiesel. Finally, the limitations of waste-based catalysts and future research directions are discussed. Research indicates that solid waste can serve as a catalyst carrier or active material for biodiesel production. Methods such as high-temperature calcination, impregnation, and coprecipitation facilitate structural modifications to the catalyst and the formation of active sites. The doping of metal ions not only alters the catalyst’s acid-base properties but also forms stable metal bonds with functional groups on the carrier, thereby maintaining catalyst stability. The application of microwave-assisted and ultrasound-assisted methods reduces reaction parameters, making biodiesel production more economical and sustainable. Overall, this study provides a scientific basis for the reuse of solid waste and ecological protection, emphasizes the development potential of waste-based catalysts in biodiesel production, and offers unique insights for innovation in this field, thereby accelerating the commercialization of biodiesel. Full article

The increasing demand for sustainable energy has spurred the exploration of advanced technologies for biodiesel production. This paper investigates the use of Dielectric Barrier Discharge (DBD)-generated low-temperature plasmas to enhance the conversion of fatty acid methyl esters (FAMEs) into hydrogenated fatty acid methyl esters (H-FAMEs) and other high-value hydrocarbons. A key mechanistic advance is achieved via in situ distillation: at the reactor temperature, unsaturated C18 and C20 FAMEs remain liquid due to their low melting points, while the corresponding saturated C18:0 and C20:0 FAMEs (with melting points of approximately 37–39 °C and 46–47 °C, respectively) solidify and deposit on a glass substrate. This phase separation continuously exposes fresh unsaturated FAME to the plasma, driving further hydrogenation and thereby delivering high overall conversion efficiency. The non-thermal, energy-efficient nature of DBD plasmas offers a promising alternative to conventional high-pressure, high-temperature methods; here, we evaluate the process efficiency, product selectivity, and scalability of this room-temperature, atmospheric-pressure approach and discuss its potential for sustainable fuel-reforming applications. Full article

This research analyzes the influence of hydroxy on pure diesel and blends of palm oil and coffee husk biodiesel with percentages of 15% and 20%. The experimental tests were carried out in a stationary diesel engine, where the torque and speed varied from 3–7 Nm and 3000–3600 rpm. Hydroxy was used as a secondary fuel with a volumetric flow injection of 4 and 8 lpm. The injection of hydroxy can reduce the BSFC and increase the BTE of the engine when running on pure diesel and biodiesel blends. The results show a maximum decrease of 11.66%, 11.28%, and 10.94% in BSFC when hydroxy is injected into D100, D85P10C5, and D80P10C10 fuels. In the case of BTE, maximum increases of 13.37%, 12.84%, and 12.34% were obtained for the above fuels. The fuels D100 + 8 lpm, D85P10C5 + 8 lpm, and D80P10C10 + 8 lpm achieved maximum energy efficiencies of 28.16%, 27.58%, and 27.32%, respectively. In the case of exergy efficiency, maximum values of 26.39%, 25.83%, and 25.58% were obtained. The environmental and social costs of CO, CO₂, and HC emissions are significantly reduced with the addition of hydroxy in pure diesel and biodiesel blends from palm oil and coffee husk. The injection of a volumetric flow rate of 8 l/min results in reductions of 11.66%, 10.61%, and 10.94% in operational cost when the engine is fueled with D100, D85P10C5, and D80P10C10, respectively, complying with standards essential for safe engine operation. In general, the research conducted indicates that hydroxy injection is a viable alternative for reducing fuel consumption and improving engine efficiency when using biodiesel blends made from palm oil and coffee husk. Full article

This study investigated the production of biodiesel from canola oil, the formulation of sustainable ternary fuel blends with diesel and alcohol (ethanol or propanol), and the experimental and machine learning-based modeling of their physical properties, including density and viscosity over a temperature range of 10 °C to 40 °C. Biodiesel was synthesized via alkali-catalyzed transesterification (6:1 methanol-to-oil molar ratio, 0.5 wt % NaOH of oil) and blended with diesel and alcohols (ethanol and propanol) in varying volume ratios. The experimental results revealed that blend density decreased from 0.8622 g/cm³ at 10 °C to 0.8522 g/cm³ at 40 °C for a blend containing ethanol. Similarly, the viscosity showed a significant reduction with temperature, e.g., the blend exhibited a viscosity decline from 8.5 mPa·s at 10 °C to 7.2 mPa·s at 40 °C. Increasing the alcohol or diesel content further reduced density and viscosity due to the lower intrinsic properties of these components. The machine learning models, Gaussian process regression (GPR), support vector regression (SVR), artificial neural networks (ANN), and decision tree regression (DTR), were applied to predict the properties of these blends. GPR demonstrated the best predictive performance for both density and viscosity. These findings confirm the strong potential of GPR for the accurate and reliable prediction of fuel blend properties, supporting the formulation of alternative fuels optimized for diesel engine performance. These aspects contribute new insights into modelling strategies for sustainable fuel formulations. Full article

Biodiesel, a renewable and environmentally friendly alternative to fossil fuels, has attracted significant attention due to its potential to reduce greenhouse gas emissions. However, high production costs and complex processing remain challenges. Heterogeneous catalysts have shown promise in overcoming these barriers by offering benefits, such as easy separation, reusability, low-cost raw materials, and the ability to reduce reaction times and energy consumption. This review evaluates key classes of heterogeneous catalysts, such as metal oxides, ion exchange resins, and zeolites, and their performance in transesterification and esterification processes. It highlights the importance of catalyst preparation methods, textural properties, including surface area, pore volume, and pore size, activation techniques, and critical operational parameters, like the methanol-to-oil ratio, temperature, time, catalyst loading, and reusability. The analysis reveals that catalysts supported on high surface area materials often achieve higher biodiesel yields, while metal oxides derived from natural sources provide cost-effective and sustainable options. Challenges, such as catalyst deactivation, sensitivity to feedstock composition, and variability in performance, are discussed. Overall, the findings underscore the potential of heterogeneous catalysts to enhance biodiesel production efficiency, although further optimization and standardized evaluation protocols are necessary for their broader industrial application. Full article

This study creates and tests a machine learning model that can predict fuel use and emissions (NO_x, CO₂, CO, HC, PN) from a marine internal combustion engine when it is running normally. The model learned from data collected from conventional diesel fuel experiments. Subsequently, we evaluated its ability to transfer by employing the parameters associated with waste cooking oil (WCO) biodiesel and its 60/40 diesel mixture. The machine learning model demonstrated exceptional proficiency in forecasting diesel mode (R² > 0.95), effectively encapsulating both long-term trends and short-term fluctuations in fuel consumption and emissions across various load regimes. Upon the incorporation of WCO data, the model maintained its capacity to identify trends; however, it persistently overestimated emissions of CO, HC, and PN. This discrepancy arose primarily from the differing chemical composition of the fuel, particularly in terms of oxygen content and density. A significant correlation existed between indicators of incomplete combustion and the utilization of fuel. Nonetheless, NO_x exhibited an inverse relationship with indicators of combustion efficiency. The findings indicate that the model possesses the capability to estimate emissions in real time, requiring only a modest amount of additional training to operate effectively with alternative fuels. This approach significantly diminishes the necessity for prolonged experimental endeavors, rendering it an invaluable asset for the formulation of fuel strategies and initiatives aimed at mitigating carbon emissions in maritime operations. Full article

The growing interest in alternative fuels stems from the need to reduce greenhouse gas emissions and promote sustainable development. Despite the dominance of fossil fuels in aviation, pulsejet engines offer a promising platform for testing new fuels due to their simple design and fuel versatility. This study presents a multi-criteria analysis of alternative fuels for use in pulsejet engines, emphasizing environmental impacts. Both gaseous (biogas, ethyne, LPG, and natural gas) and liquid fuels (methanol, ethanol, biodiesel, Jet A-1, and SAF) were examined. Exhaust emissions (CO₂, H₂O, CO) were simulated in Ansys 2025 based on literature data and chemical calculations. Additional factors analyzed included calorific value, production cost, thermal expansion, density, life cycle emissions (LCA), CO₂ emissions per fuel mass, and renewable energy content. Using the zero-unitization method, results were normalized into a single aggregate variable for each fuel. The highest values were recorded for biogas and methanol, respectively, indicating their potential as alternative fuels. The findings support further development of sustainable fuels for pulsejet engines. Future research should address combustion optimization and noise reduction, enhancing viability in aviation and other transport sectors. Integration with the current fuel infrastructure is also recommended to facilitate broader implementation. Full article

As a renewable alternative to fossil fuels, the industrial production of biodiesel urgently requires the development of efficient and recyclable solid base catalysts. In this study, the physicochemical properties and catalytic performance differences between MgO/Na₂CO₃ and MgO/K₂CO₃ catalysts were systematically compared using soybean oil as the raw material. By regulating the calcination temperature (500–700 °C), alcohol-to-oil ratio (3:1–24:1), and metal carbonate loading (10–50%), combined with N₂ adsorption–desorption, CO₂-TPD, XRD, SEM-EDS, and cycling experiments, the regulatory mechanisms of the ionic radius differences between sodium and potassium on the catalyst structure and performance were revealed. The results showed that MgO/Na₂CO₃-600 °C achieved a FAME yield of 97.5% under optimal conditions, which was 1.7% higher than MgO/K₂CO₃-600 °C (95.8%); this was attributed to its higher specific surface area (148.6 m²/g vs. 126.3 m²/g), homogeneous mesoporous structure, and strong basic site density. In addition, the cycle stability of MgO/K₂CO₃ was significantly lower, retaining only 65.2% of the yield after five cycles, while that of MgO/Na₂CO₃ was 88.2%. This stability difference stems from the disparity in their solubility in the reaction system. K₂CO₃ has a higher solubility in methanol (3.25 g/100 g at 60 °C compared to 1.15 g/100 g for Na₂CO₃), which is also reflected in the ion leaching rate (27.7% for K⁺ versus 18.9% for Na⁺). This study confirms that Na⁺ incorporation into the MgO lattice can optimize the distribution of active sites. Although K⁺ surface enrichment can enhance structural stability, the higher leaching rate leads to a rapid decline in catalyst activity, providing a theoretical basis for balancing catalyst activity and durability in sustainable biodiesel production. Full article

Hydrotreated Vegetable Oil (HVO) is one of the solutions for replacing fossil diesel with a clean and renewable fuel in compression ignition (CI) engines. This study focuses on the benefits of using HVO-fueled engines in Brazil concerning CO₂ emissions, compared with other alternatives in the Brazilian energy matrix. The analysis includes CO₂ emissions from the Brazilian diesel fleet over the last 10 years considering conventional diesel fuel, traditional biofuels, and the anticipated introduction of HVO into the Brazilian market. The proposal involves neat HVO as well as blends of fossil diesel, biodiesel, and HVO (up to 50% by vol.), these blends being more realistic for their practical deployment. Considering the Brazilian diesel fleet over the past 10 years (2015–2025), net CO₂ emissions would have been reduced by 77.4% if 100% HVO had been used, while a reduction of 54.4% would have occurred with the blend containing 50% of HVO. Moreover, the use of 100% HVO for this fleet from 2015 would lead to 366.5 and 652.4 Mton of CO₂ in 2030 and 2035, respectively, compared with 1621.5 and 2885.9 Mton if 100% fossil diesel is used. The economic analysis suggests that fuel cost savings of approximately 12 USD billion could be reached in 2035 under favorable HVO production scenarios. This is a favorable projection, with positive values for all blends and pure HVO, indicating economic feasibility. Full article

The presented research examined the impact of using biodiesel as a fuel for existing diesel engines during the transition to the broader adoption of electric vehicles powered by renewable energy or through integrated hybrid drive systems. The authors considered previous research on this topic, which is demonstrated by a literature review. This paper will utilize the findings to further explore the potential of optimizing existing engines by using biodiesel and thus propose their continued use in the transition period as one of the clean fuels. This paper outlines the standards that define fuel quality and presents a test bench equipped with an experimental engine and specialized equipment for laboratory examination, enabling the measurement of emissions and the determination of cylinder pressure. To ensure the repeatability of the experimental conditions and facilitate future comparison of the obtained results, the engine examination was conducted according to the standard ESC 13-mode test. The examination process confirmed a significant reduction in particulate matter emissions (on average 40%) but, simultaneously, an increase in nitrogen oxide emissions (on average 25%), whose level, according to data from the literature, depends on the type of raw materials used for biodiesel production. Brake thermal efficiency is higher when operating with biodiesel (on average 1.5%). Still, it was concluded that the use of biodiesel in existing diesel engines is feasible only if the engines are equipped with variable systems for automatically adjusting the compression ratio, fuel injection time, valve timing, and so on. The outcomes from the examination conducted can be further processed by applying statistical methods and represent an essential database for further research in this scientific area. Full article

Varshavskii’s ‘Diffusion Theory’, less investigated due to its limited international visibility, can offer one of the simplest and, on the other hand, high-accuracy methods for evaluating the ignition delay of fossil fuel and biofuel droplets, including their blend. In this study, experimental pre-tests were conducted to determine pre-existing subject knowledge on stationary droplet combustion at ambient pressure and temperatures varying from 935 to 1010 K followed by simulation of droplet ignition times. The test fuels were mineral diesel (DF), RME and a 20% RME blend with DF. Simulations were performed for isobaric conditions. Using the detailed transport model and detailed chemical kinetics, the necessary rearrangements were made for the governing equations to meet the criteria for modern fuels (biodiesel, diesel, and blend). The influence of different physical parameters, such as droplet radius, or initial conditions, on the ignition delay time was investigated. The high sensitivity of the proposed methodology to experimental results was substantiated. Full article

The 83rd session of the IMO Maritime Environment Protection Committee (MEPC 83) approved a global pricing mechanism for the shipping industry, with formal adoption scheduled for October 2025. Proposed mechanisms include the International Maritime Sustainable Fuels and Fund (IMSF&F) and a combined approach integrating GHG Fuel Standards with Universal GHG Contributions (GFS&UGC). This study developed a model based on the marginal abatement cost curve (MACC) methodology to assess the cost-effectiveness of alternative fuels under both mechanisms. Sensitivity analyses evaluated the impacts of fuel prices, carbon prices, and the GHG Fuel Intensity (GFI) indicator on MAC. Results indicate that implementing the GFS&UGC mechanism yields higher net present values (NPVs) and lower MACs compared to IMSF&F. Introducing universal GHG contributions promotes a comparatively fairer transition to sustainable shipping fuels. Investments in zero- or near-zero-fueled (ZNZ) ships are unlikely to be recouped by 2050 unless carbon prices rise sufficiently to boost revenues. Bio-Methanol and bio-diesel emerged as the most cost-competitive ZNZ options in the long term, while e-Methanol’s poor competitiveness stems from its extremely high price. Both pooling costs and universal GHG levies significantly reduce LNG’s economic viability over the study period. MACs demonstrated greater sensitivity to fuel prices (P_fuel) than to carbon prices (P_carbon) or GFI within this study’s parameterization scope, particularly under GFS&UGC. Ratios of P_carbon%/P_fuel% in equivalent sensitivity scenarios were quantified to determine relative price importance. This work provides insights into fuel selection for shipping companies and supports policymakers in designing effective GHG pricing mechanisms. Full article

This review article provides a comprehensive analysis of the recent advancements in combustion science and engineering, focusing on the application of machine learning and genetic algorithms from 2015 to 2024. The study examines the integration of computational methods, including computational fluid dynamics, neural networks, and genetic algorithms, with various fuel types such as biodiesel, biomass, coal, gasoline, hydrogen, and natural gas. A systematic search in the Scopus database identified relevant articles, which were categorized based on fuel types and computational methodologies. The analysis covers key areas such as combustion modelling and simulation, engine applications, alternative fuels, pollutant control, and industrial combustion systems. This review highlights the growing role of machine learning and genetic algorithms in enhancing combustion efficiency, reducing emissions, and optimizing energy production, providing insights into the current state of the art and future trends in this critical field. The study further examines the geographical distribution of research, noting significant contributions from Canada, China, France, Germany, India, Iran, Japan, Malaysia, Pakistan, Saudi Arabia, the United Kingdom, and the United States, alongside other international contributions. A total of 165 peer-reviewed articles were analyzed, covering a range of combustion scenarios and fuel types. The most frequently applied methods include artificial neural networks (ANNs), support vector machines (SVMs), and random forests (RFs) for predictive modeling, as well as genetic algorithms (GAs) for system optimization. ANN-based models achieved high accuracy in predicting NO_x emissions and flame speed, with some studies reporting mean absolute errors below 5%. GA methods demonstrated effectiveness in fuel blend optimization and geometry design, achieving emission reductions of up to 30% in experimental setups. This review also highlights persistent challenges such as data availability, model generalization, and reproducibility, and proposes future directions toward more interpretable and standardized applications of ML/GA in combustion science. Full article