Abstract: The stability of the dumbbell structure has been confirmed by previous theory and experiment. Based on firstprinciples calculations, we proposed hexagonal dumbbell graphene (HDB C10) and rectangular dumbbell graphene (RDB C10) monolayers containing periodically raised C (CR) atoms. They turn out to have high mobility semiconductor properties. By adsorbing H atoms on these CR atoms, their band structures can be widely tuned from semiconductor to semimetal. When considering adsorption of two/four H atoms on the unit cell of the dumbbell structure, the bandgap can be increased, and isolated flat band structures can be obtained by further adding or removing H atoms. Remarkably, two different Dirac band structures can be found in the HDB/RDB C10H2-I monolayers. The HDB C10H2-I shows a Dirac cone with isotropic Fermi velocities, while the RDB C10H2-I monolayer exhibits a quasi-one-dimensional Dirac nodal line with varying Fermi velocities along the XS path. Tight-binding (TB) models are constructed including nearest neighbor (NN) and next NN hopping in order to understand our DFT results. These TB models are related to the Su-Schrieffer-Heeger model, and are able to explain the tunable topological properties of the RDB C10H2-I monolayer. They not only are able to explain the different kinds of Fermi velocity, but also can predict the emergence of topological edge states, providing a good platform for research on Dirac fermions. The HDB/RDB C10 monolayer exhibits more freedom of tunable band structures and more stable hydrogen storage capacity, making it superior to graphene. Finally, possible experimental synthesis paths of these DB monolayers are provided.

Abstract: Cu is one of the most promising materials as an electrocatalyst for the nitrate reduction reaction (NO3RR) to ammonia, a reaction that can simultaneously remove nitrates from wastewater and produce ammonia, a high-value commodity chemical. However, a rational approach to catalyst design is lacking, limiting efficient catalyst optimization. In this work, we propose a way to synthesize monodisperse, polycrystalline Cu NPs with small variances in size by changing the carbon chain length of the phosphonic acid-based ligand. Cu NPs with 8.3, 10.0, and 11.9 nm diameters are successfully synthesized, and high-resolution electron microscopy and tomography are used to characterize these NPs in depth. By isolating Cu NP size as a parameter, we can unequivocally establish its effect on electrochemical performance for the NO3RR to ammonia under optimal operating conditions for the catalyst (0.1 M KOH electrolyte at -1.25 V vs RHE, as established in the first phase). The smallest Cu NPs (8.3 nm with a TDPA ligand) perform best, achieving Faradaic efficiencies (FEs) of 85.4% and absolute current densities of similar to 250 mA cm(-2), with increasing current densities and constant FEs as the particle size decreases. To allow for a rational approach to Cu-based catalyst design from a stability perspective, this work completed a first study of the main degradation pathway that the Cu NPs undergo during NO3RR. High-resolution electron microscopy and tomography are used to characterize the particles at various stages of the reaction. The NPs undergo agglomeration, pulverization, and particle detachment due to the reaction, starting at a particle size of 8.3 nm and progressively getting smaller, but leveling off, until a NP size of 2.6 nm is reached after 2 h of electrolysis. This decrease in NP size goes paired with a decrease in FE from 83% after the first 15 min to 74% after 2 h at -0.75 V vs RHE, despite the increase in active surface area. These insights into the most prominent degradation mechanisms allow for rational adjustments to future catalysts to combat these changes; for example, by embedding NPs in a tailored support, morphological degradation could be impeded. Therefore, these insights allow for a rational approach to the improvement of the stability of Cu-based catalysts for the NO3RR, a very important but often an overlooked aspect of catalyst design.

Abstract: Winter peaks in Belgian electricity demand are significantly higher than the summer peaks, creating a greater potential for imbalances between demand and supply. This potential is exacerbated because of the risk of outages in its ageing nuclear power plants, which are being phased out in the medium term. This paper conducts a choice experiment to investigate the acceptability of a load control-based demand response program in the winter months. It surveys 186 respondents on their willingness to accept limits on the use of home appliances in return for a compensation. Results indicate that respondents are most affected by the days of the week that their appliance usage would be curtailed, and by the compensation they would receive. The willingness to enroll in a program increases with age, environmental consciousness, home ownership, and lower privacy concerns. The analysis predicts that 95% of the sample surveyed could enroll in a daily load control program for a compen- sation of €41 per household per year. Thus while an initial rollout among older and more pro-environment homeowners could be successful, a wider implementation would require an explanation of its environmental and financial benefits to the population, and a greater consideration of their data privacy concerns.

Abstract: Maritime shipping is a key factor that enables the global economy, however the pressure it exerts on the environment is increasing rapidly. In order to reduce the emissions of harmful greenhouse gasses, the search is on for alternative fuels for the maritime shipping industry. In this work the usefulness of hydrogen and hydrogen carriers is being investigated as a fuel for sea going ships. Due to the low volumetric energy density of hydrogen under standard conditions, the need for efficient storage of this fuel is high. Key processes in the use of hydrogen are discussed, starting with the production of hydrogen from fossil and renewable sources. The focus of this review is different storage methods, and in this work we discuss the storage of hydrogen at high pressure, in liquefied form at cryogenic temperatures and bound to liquid or solid-state carriers. In this work a theoretical introduction to different hydrogen storage methods precedes an analysis of the energy-efficiency and practical storage density of the carriers. In the final section the major challenges and hurdles for the development of hydrogen storage for the maritime industry are discussed. The most likely challenges will be the development of a new bunkering infrastructure and suitable monitoring of the safety to ensure safe operation of these hydrogen carriers on board the ship.

Abstract: Correction for ‘From the Birkeland–Eyde process towards energy-efficient plasma-based NO_{<italic>X</italic>}synthesis: a techno-economic analysis’ by Kevin H. R. Rouwenhorst<italic>et al.</italic>,<italic>Energy Environ. Sci.</italic>, 2021,<bold>14</bold>, 2520–2534, https://doi.org/10.1039/D0EE03763J.

Abstract: Plasma-catalytic dry reforming of CH4 (DRM) is promising to convert the greenhouse gasses CH4 and CO2 into value-added chemicals, thus simultaneously providing an alternative to fossil resources as feedstock for the chemical industry. However, while many experiments have been dedicated to plasma-catalytic DRM, there is no consensus yet in literature on the optimal choice of catalyst for targeted products, because the underlying mechanisms are far from understood. Indeed, plasma catalysis is very complex, as it encompasses various chemical and physical interactions between plasma and catalyst, which depend on many parameters. This complexity hampers the comparison of experimental results from different studies, which, in our opinion, is an important bottleneck in the further development of this promising research field. Hence, in this perspective paper, we describe the important physical and chemical effects that should be accounted for when designing plasma-catalytic experiments in general, highlighting the need for standardized experimental setups, as well as careful documentation of packing properties and reaction conditions, to further advance this research field. On the other hand, many parameters also create many windows of opportunity for further optimizing plasma-catalytic systems. Finally, various experiments also reveal the lack of improvement in plasma catalysis compared to plasma-only, specifically for DRM, but the underlying mechanisms are unclear. Therefore, we present our newly developed coupled plasma-surface kinetics model for DRM, to provide more insight in the underlying reasons. Our model illustrates that transition metal catalysts can adversely affect plasmacatalytic DRM, if radicals dominate the plasma-catalyst interactions. Thus, we demonstrate that a good understanding of the plasma-catalyst interactions is crucial to avoiding conditions at which these interactions negatively affect the results, and we provide some recommendations for improvement. For instance, we believe that plasma-catalytic DRM may benefit more from higher reaction temperatures, at which vibrational excitation can enhance the surface reactions.

Abstract: This study investigates the dry reformation of methane (DRM) over Ni/Al2O3 catalysts in a dielectric barrier discharge (DBD) non-thermal plasma reactor. A novel hybrid machine learning (ML) model is developed to optimize the plasma-catalytic DRM reaction with limited experimental data. To address the non-linear and complex nature of the plasma-catalytic DRM process, the hybrid ML model integrates three well-established algorithms: regression trees, support vector regression, and artificial neural networks. A genetic algorithm (GA) is then used to optimize the hyperparameters of each algorithm within the hybrid ML model. The ML model achieved excellent agreement with the experimental data, demonstrating its efficacy in accurately predicting and optimizing the DRM process. The model was subsequently used to investigate the impact of various operating parameters on the plasma-catalytic DRM performance. We found that the optimal discharge power (20 W), CO2/CH4 molar ratio (1.5), and Ni loading (7.8 wt%) resulted in the maximum energy yield at a total flow rate of
51 mL/min. Furthermore, we investigated the relative significance of each operating parameter on the performance of the plasmacatalytic DRM process. The results show that the total flow rate had the greatest influence on the conversion, with a significance exceeding 35% for each output, while the Ni loading had the least impact on the overall reaction performance. This hybrid model demonstrates a remarkable ability to extract valuable insights from limited datasets, enabling the development and optimization of more efficient and selective plasma-catalytic chemical processes.