Abstract: Electrification and carbon capture technologies are essential for achieving net-zero emissions in the chemical sector. A crucial strategy involves converting captured CO2 into CO, a valuable chemical feedstock. This study evaluates the feasibility of two innovative methods: plasma activation and electrolysis, using clean electricity and captured CO2. Specifically, it compares a gliding arc plasma reactor with an embedded novel carbon bed system to a modern zero-gap type low-temperature electrolyser. The plasma method stood out with an energy cost of 19.5 GJ per tonne CO, marking a 43% reduction compared to electrolysis and conventional methods. CO production costs for plasma- and electrolysis-based plants were $671 and $962 per tonne, respectively. However, due to high uncertainty regarding electrolyser costs, the CO production costs in electrolysis-based plants may actually range from $570 to $1392 per tonne. The carbon bed system in the plasma method was a key factor in facilitating additional CO generation from O-2 and enhancing CO2 conversion, contributing to its cost-effectiveness. Challenges for electrolysis included high costs of equipment and low current densities. Addressing these limitations could significantly decrease production costs, but challenges arise from the mutual relationship between intrinsic parameters, such as CO2 conversion, CO2 input flow, or energy cost. In a future scenario with affordable feedstocks and equipment, costs could drop below $500 per tonne for both methods. While this may be more challenging for electrolysis due to complexity and expensive catalysts, plasma-based CO production appears more viable and competitive.

Abstract: Despite the recent promising potential of plasma-based nitrogen fixation, the technology faces significant challenges in efficient upscaling. To tackle this challenge, we investigate two reactors, i.e., a small one, operating in a flow rate range of 5-20 ln min-1 and current range of 200-500 mA, and a larger one, operating at higher flow rate (100-300 ln min-1) and current (400-1000 mA). Both reactors operate in a pin-to-pin configuration and are powered by direct current (DC) from the same power supply unit, to allow easy comparison and evaluate the effect of upscaling. In the small reactor, we achieve the lowest energy cost (EC) of 2.8 MJ mol-1, for a NOx concentration of 1.72%, at a flow rate of 20 ln min-1, yielding a production rate (PR) of 33 g h-1. These values are obtained in air; in oxygen-enriched air, the results are typically better, at the cost of producing oxygen-enriched air. In the large reactor, the higher flow rates reduce the NOx concentration due to lower SEI, while maintaining a similar EC. This stresses the important effect of the geometrical configuration of the arc, which is typically concentrated in the center of the reactor, resulting in limited coverage of the reacting gas flow, and this is identified as the limiting factor for upscaling. However, our experiments reveal that by changing the reactor configuration, and thus the plasma geometry and power deposition mechanisms, the amount of gas treated by the plasma can be enhanced, leading to successful upscaling. To obtain more insights in our experiments, we performed thermodynamic equilibrium calculations. First of all, they show that our measured lowest EC closely aligns with the calculated minimum thermodynamic equilibrium at atmospheric pressure. In addition, they reveal that the limited NOx production in the large reactor results from the contracted nature of the plasma. To solve this limitation, we let the large reactor operate in so-called torch configuration. Indeed, the latter enhances the NOx concentrations compared to the pin-to-pin configuration, yielding a PR of 80 g h-1 at an EC of 2.9 MJ mol-1 and NOx concentration of 0.31%. This illustrates the importance of reactor design in upscaling. With the focus on feasibility evaluation of scaling-up plasma-based nitrogen fixation by combined experiments and thermodynamic modelling, we aim to tackle the challenge of design and development of an energy-efficient and scaled-up plasma reactor.

Abstract: Lignocellulosic biomass is the most abundant source of renewable biomass and is seen as a high-potential replacement for petroleum-based resources. The conversion technologies to advanced biofuels are still at a low maturity level, thus allowing for future cost reductions through technological learning. This fact is barely considered in state-of-the-art techno-economic assessments and a structured approach to account for technological learning in techno-economic assessments is needed. In this study, a framework for techno-economic assessments of advanced biofuels, integrating learning curves, is proposed. As a validation of this framework, the economic feasibility of the valorization of corn stover for the production of second-generation bioethanol in Belgium is studied. Process flowsheet simulations in Aspen Plus are developed, with an emphasis on the comparison of four different pretreatment technologies and two plant capacities at 156 dry kt biomass/y and 667 dry kt/y. The dilute acid pretreatment model of the large-scale biorefinery required the lowest minimum learning rate to reach an economically feasible biorefinery by 2030, being 3.9%, almost half as the one calculated for the smaller scale plant. This learning rate seems to be achievable based on learning rates commonly estimated in literature. We conclude that there is a potential for advanced ethanol production in Belgium under the current state of technology for large-scale biorefineries, which require additional biomass imports, when accounting for future cost reductions through learning

Abstract: Multi-objective optimization is an important decision-making tool for energy processes, as multiple targets need to be achieved. These objectives are usually conflicting since a single solution cannot be optimal for all objectives, resulting in a set of Pareto-optimal solutions. Multiple indicators might be available to describe a sustainability objective, such as the environmental impact which is commonly evaluated by performing a life cycle assessment. In this study, Pareto aggregation is proposed as a method which employs a novel multi-objective optimization-based approach as an alternative to the classically used aggregation in life cycle assessment. This method identifies conflicting environmental indicators and performs an aggregation among those that require a trade-off. An environmental-economic optimization of a second-generation bioethanol plant is used to illustrate and evaluate the proposed method. Process parameters from a biochemical conversion pathway flowsheet simulation model are chosen as optimization variables. To reduce the computational time, surrogate models, based on artificial neural networks, are used. Out of the eighteen ReCiPe Midpoint environmental indicators, five were identified as conflicting, resulting in an aggregated environmental objective, which was then traded off with the economic objective function, chosen as the levelized cost of ethanol. Comparison with the widely used single-score EcoIndicator99 showed that the Pareto aggregation method can reduce most of the environmental indicators by up to 6.5%. This research provides an insight on non-redundant objective functions, aiming at reducing the dimensionality of multi-objective optimization problems, while taking into consideration decision-makers’ preferences.

Abstract: This study introduces solid-state tuning of a mesostructured cellular foam (MCF) to enhance hydrogen (H-2) storage in clathrate hydrates. Grafting of promoter-like molecules (e.g., tetrahydrofuran) at the internal surface of the MCF resulted in a substantial improvement in the kinetics of formation of binary H-2-THF clathrate hydrate. Identification of the confined hydrate as sII clathrate hydrate and enclathration of H-2 in its small cages was performed using XRD and high-pressure H-1 NMR spectroscopy respectively. Experimental findings show that modified MCF materials exhibit a similar to 1.3 times higher H-2 storage capacity as compared to non-modified MCF under the same conditions (7 MPa, 265 K, 100% pore volume saturation with a 5.56 mol% THF solution). The enhancement in H-2 storage is attributed to the hydrophobicity originating from grafting organic molecules onto pristine MCF, thereby influencing water interactions and fostering an environment conducive to H-2 enclathration. Gas uptake curves indicate an optimal tuning point for higher H-2 storage, favoring a lower density of carbon per nm(2). Furthermore, a direct correlation emerges between higher driving forces and increased H-2 storage capacity, culminating at 0.52 wt% (46.77 mmoles of H-2 per mole of H2O and 39.78% water-to-hydrate conversions) at 262 K for the modified MCF material with fewer carbons per nm(2). Notably, the substantial H-2 storage capacity achieved without energy-intensive processes underscores solid-state tuning's potential for H-2 storage in the synthesized hydrates. This study evaluated two distinct kinetic models to describe hydrate growth in MCF. The multistage kinetic model showed better predictive capabilities for experimental data and maintained a low average absolute deviation. This research provides valuable insights into augmenting H-2 storage capabilities and holds promising implications for future advancements.

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.