Fuels, Volume 4, Issue 3 (September 2023) – 7 articles

Hydrogen sulfide (H₂S) is considered a toxic and corrosive gas, commonly found in natural gas, crude oil, and other fossil fuels. This corrosive gas may lead to stress corrosion cracking (SCC). This phenomenon is caused by the combined influence of tensile stress and a corrosive environment. This may lead to the sudden failure of normally ductile metal alloys, especially at an elevated temperature. Desulfurization is the process of removing H₂S from these fuels to reduce their harmful environmental and health impacts. Ionic liquids (ILs) have shown great potential for application as liquid absorbents for H₂S extraction because of their advantages such as non-volatility, functionality, high carbon solubility and low energy requirements for regeneration. The proposed hydrogen sulfide extraction system consists of a tube, membrane and shell. 1-ethyl-3-methylimidazolium (emim)-based ionic liquids with bis-(trifluoromethyl) sulfonylimide (NTf2) anion has been selected due to its high H₂S diffusion coefficient. Functionalized graphene oxide (GO) advanced membranes have been employed in this design. In this research, H₂S extraction with ionic liquids has been numerically studied. The COMSOL finite element and multi-physics code has been employed to solve the continuity, turbulent fluid flow (k-ε model), and transient diffusion equations. For small time periods, there is sharp gradient in H₂S concentration profile inside the shell section. This is because the diffusion coefficient of H₂S in the ionic liquid is very small and the shell section is much thicker than the membrane. It has been determined that H₂S is absorbed almost completely by ionic liquids after a time period of 30,000 s. Full article

The cost of transport decarbonisation matters, yet little information is available. Policies need to reflect the costs to society. The European Union relies on the PRIMES model, a private model with limited transparency. Our research revealed its methodological deficiencies. Based on a revised PRIMES model, modelling was carried out and compared with an official impact assessment prepared for a key EU policy. Our modelling results indicate that crop-based bioethanol has negative abatement costs, biodiesel and biomethane have costs below 100 EUR/tCO2eq, electromobility falls in the range of 100–150 EUR/tCO2eq, cellulosic ethanol has costs above 200 EUR/tCO2eq, while advanced biodiesel has costs above 300 EUR/tCO2eq. Our results on carbon abatement costs suggest that policy-making has often been based on outdated modelling in the EU. With regard to transport decarbonisation policies, a large number of recent energy and climate proposals by the European Commission seem to have been misguided. Full article

Fracture porosity is crucial for storage and production efficiency in fractured tight reservoirs. Geophysical image logs using resistivity measurements have traditionally been used for fracture characterization. This study aims to develop a novel, hybrid machine-learning method to predict fracture porosity using conventional well logs in the Ahnet field, Algeria. Initially, we explored an Artificial Neural Network (ANN) model for regression analysis. To overcome the limitations of ANN, we proposed a hybrid model combining Support Vector Machine (SVM) classification and ANN regression, resulting in improved fracture porosity predictions. The models were tested against logging data by combining the Machine Learning approach with advanced logging tools recorded in two wells. In this context, we used electrical image logs and the dipole acoustic tool, which allowed us to identify 404 open fractures and 231 closed fractures and, consequently, to assess the fracture porosity. The results were then fed into two machine-learning algorithms. Pure Artificial Neural Networks and hybrid models were used to obtain comprehensive results, which were subsequently tested to check the accuracy of the models. The outputs obtained from the two methods demonstrate that the hybridized model has a lower Root Mean Square Error (RMSE) than pure ANN. The results of our approach strongly suggest that incorporating hybridized machine learning algorithms into fracture porosity estimations can contribute to the development of more trustworthy static reservoir models in simulation programs. Finally, the combination of Machine Learning (ML) and well log analysis made it possible to reliably estimate fracture porosity in the Ahnet field in Algeria, where, in many places, advanced logging data are absent or expensive. Full article

Biogas and hydrogen (H₂) are breaking through as alternative energy sources in road transport, specifically for heavy-duty vehicles. Until a public network of service stations is deployed for such vehicles, the owners of large fleets will need to build and manage their own refueling facilities. Fleet refueling management and remote monitoring at these sites will become key business needs. This article describes the construction of a prototype system capable of solving those needs. During the design and development process of the prototype, the standard industry protocols involved in these installations have been considered, and the latest expertise in information technology systems has been applied. This prototype has been essential to determine the Strengths, Challenges, Opportunities and Risks (SCOR) of such a system, which is the first step of a more ambitious project. A second stage will involve setting up a pilot study and developing a commercial system that can be widely installed to provide a real solution for the industry. Full article

The present study aims to analyze the performance characteristics of the biogas dry reforming process conducted in a membrane reactor using Ni/Cr catalysts and to compare these characteristics with those obtained using pure Ni catalysts. The effect of the pre-set reaction temperature, the molar ratio of CH₄:CO₂ and the pressure difference between the reaction chamber and the sweep chamber on the characteristics of biogas dry reforming is analyzed. In the present work, the molar ratio of the supplied CH₄:CO₂ is varied to 1.5:1, 1:1 and 1:1.5. In this case, CH₄:CO₂ = 1.5:1 simulates a biogas. The pressure difference between the reaction chamber and the sweep chamber is varied to 0 MPa, 0.010 MPa and 0.020 MPa. The reaction temperature is changed to 400 °C, 500 °C and 600 °C. It is revealed that the highest concentration of H₂ is achieved using a Ni/Cr catalyst when the molar ratio of CH₄:CO₂ is 1.5:1 at the differential pressure of 0.010 MPa and the reaction temperature of 600 °C. Under this condition, the H₂ yield, H₂ selectivity and thermal efficiency are 12.8%, 17.5% and 174%, respectively. The concentration of the H₂ produced using a Ni/Cr catalyst is larger than that produced using a Ni catalyst regardless of the pre-set reaction temperature, the molar ratio of CH₄:CO₂ and the differential pressure. Full article

Detecting and identifying hydrogen gas leakage before a potential disaster is a critical safety concern. To address this issue, a low-cost and simple-design sensor is required with high response and fast sensing time, capable of detecting hydrogen gas even at low concentrations of 5–500 ppm. This study investigates the use of magnetron-sputtered SnO₂ thin films with palladium as a catalytic layer to achieve better sensing output. The developed Pd-caped SnO₂ thin film sensors showed increased sensitivity with increasing thickness, up to 246.1 nm at an operating temperature of 250 °C. The sensor with a thickness of 246.1 nm exhibited excellent selectivity for H₂ gas, even in humid conditions, and was able to distinguish it from other gases such as CO, NH₃, and NO₂. The sensor demonstrated high response (99%) with a response/recovery time of 58 s/35 s for (5–500 ppm) hydrogen gas. The sensor showed linear response to H₂ gas concentration variation (5–500 ppm) at 250 °C. The sensor was found to be mechanically stable even after 60 days in a high-humidity environment. The LOD of sensor was 151.6 ppb, making it a suitable candidate for applied sensing applications. The Pd-caped SnO₂ thin film sensor with thickness of ~245 nm could potentially improve the safety of hydrogen gas handling. Full article

The transition of mobility (in German “Verkehrswende”) as a fundamental part of the overall energy transition is a controversial field among stakeholders—in particular when it comes to synthetic fuels. There are considerable opposing views on the pros and cons of synthetic fuels within stakeholder communication. Against this background, the aim of this study was to research stakeholder positions and communication by identifying, systemizing, and assessing the bandwidth of stakeholder statements and views in Germany using a document-based positioning analysis. The objective was to provide the broadest possible range of (controversial) assessments on synthetic fuels’ future pathways. Based on a document analysis of 41 sources published by 17 stakeholders from the areas of economy, environment, and civil society in the last ten years, we analyzed commonalities and differences in the assessments of the synthetic fuels’ path as well as the reasons behind it. The results were synthesized in three narrative frames dominating the German discourse on synthetic fuels, namely: (1) synthetic fuels as a key component for the mobility transition; (2) synthetic fuels as an essential strategic niche management component, and (3) mobility transition as sustainable, affordable, safe, and comfortable mobility—with or without synthetic fuels. Full article