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 slow photon effect, a structural effect of photonic crystal photocatalyst, is very efficient in the enhancement of photocatalytic reactions. However, slow photons in powdered photonic crystal photocatalyst have rarely been discussed because they are usually randomly oriented when the photocatalytic reaction happens in solution under constant stirring. In this work, for the first time we design a gradient ternary TiO2-Au-CdS photonic crystal based on three-dimensionally ordered macroporous (3DOM) TiO2 as skeleton, Au as electron transfer medium and CdS as active material for photocatalytic H2 production under visible-light. As a result, this gradient ternary photocatalyst is favorable to simultaneously enhance light absorption, extend the light responsive region and reduce the recombination rate of the charge carriers. In particular, we found that slow photons at blue-edge exhibit much higher photocatalytic activity than that at red-edge. The photonic crystal photocatalyst with a macropore size of 250 nm exhibits the highest visible-light H2 production rate of 3.50 mmolh⁻¹g⁻¹ due to the slow photon energy at the blue-edge to significantly enhance the incident photons utilization. This work verifies that slow photons at the blue-edge can largely enhance light harvesting and sheds a light on designing the powdered photonic crystal photocatalyst to promote the photocatalytic H2 production via slow photon effect.

Abstract: Multiple electrochemical processes are involved at the catalyst/ electrolyte interface during the oxygen evolution reaction (OER). With the purpose of elucidating the complexity of surface dynamics upon OER, we systematically studied two Ni-based crystalline oxides (LaNiO3−δ and La2Li0.5Ni0.5O4) and compared them with the state-of-the-art Ni−Fe (oxy)- hydroxide amorphous catalyst. Electrochemical measurements such as rotating ring disk electrode (RRDE) and electrochemical quartz microbalance microscopy (EQCM) coupled with a series of physical characterizations including transmission electron microscopy (TEM) and X-ray absorption spectroscopy (XAS) were conducted to unravel the exact pH effect on both the OER activity and the catalyst stability. We demonstrate that for Ni-based crystalline catalysts the rate for surface degradation depends on the pH and is greater than the rate for surface reconstruction. This behavior is unlike that for the amorphous Ni oxyhydroxide catalyst, which is found to be more stable and pH-independent.

Abstract: Global environmental problems have urged the need for developing sustainable technologies. However, new technologies that enter the market have often higher economic costs and potentially higher environmental impacts than conventional technologies. This can be explained by learning effects: a production process that is performed for the first time runs less smooth than a production process that has been in operation for years. To obtain a fair estimation of the potential of a new technology, learning effects need to be included. A review on the current literature on learning effects was conducted in order to provide guidelines on how to include learning effects in prospective technology assessment. Based on the results of this review, five recommendations have been formulated and an integration of learning effects in the structure of prospective technology assessment has been proposed. These five recommendations include the combined use of learning effects on the component level and on the end product level; the combined use of learning effects on the technical, economic and environmental level; the combined use of extrapolated values and expert estimates; the combined use of learning-by-doing and learning-by-searching effects and; a tier-based method, including quality criteria, to calculate the learning effect. These five complementary strategies could lead to a clearer perspective on the environmental impact and cost structure of the new technology and a fairer comparison base with conventional technologies, potentially resulting in a faster adoption and a shorter time-to-market for sustainable technologies.

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: Wide band gap thin-film kesterite solar cell based on non-toxic and earth-abundant materials might be a suitable candidate as a top cell for tandem configuration in combination with crystalline silicon as a bottom solar cell. For this purpose and based on parameters we have extracted from electrical and optical characterization techniques of Cu2ZnGeSe4 absorbers and solar cells, a model has been developed to describe the kesterite top cell efficiency limitations and to investigate the different possible configurations with transparent back contact for fourterminal tandem solar cell application. Furthermore, we have studied the tandem solar cell performance in view of the band gap and the transparency of the kesterite top cell and back contact engineering. Our detailed analysis shows that a kesterite top cell with efficiency > 14%, a band gap in the range of 1.5-1.7 eV and transparency above 80% at the sub-band gaps photons energies are required to achieve a tandem cell with higher efficiency than with a single silicon solar cell.

Abstract: Development of low-cost and high-performance oxygen evolution reaction catalysts is key to implementing polymer electrolyte membrane water electrolyzers for hydrogen production. Iridium-based oxides are the state-of-the-art acidic oxygen evolution reactio catalysts but still suffer from inadequate activity and stability, and iridium's scarcity motivates the discovery of catalysts with lower iridium loadings. Here we report a mass-selected iridium-tantalum oxide catalyst prepared by a magnetron-based cluster source with considerably reduced noble-metal loadings beyond a commercial IrO2 catalyst. A sensitive electrochemistry/mass-spectrometry instrument coupled with isotope labelling was employed to investigate the oxygen production rate under dynamic operating conditions to account for the occurrence of side reactions and quantify the number of surface active sites. Iridium-tantalum oxide nanoparticles smaller than 2 nm exhibit a mass activity of 1.2 ± 0.5 kA “g” _“Ir” ^“-1” and a turnover frequency of 2.3 ± 0.9 s-1 at 320 mV overpotential, which are two and four times higher than those of mass-selected IrO2, respectively. Density functional theory calculations reveal that special iridium coordinations and the lowered aqueous decomposition free energy might be responsible for the enhanced performance.

Abstract: For oxygen conducting materials applied in solid oxide fuel cells and chemical-looping processes, the understanding of the oxygen diffusion mechanism and the materials’ crystal structure at different stages of the redox reactions is a key parameter to control their performance. In this paper we report the first ever in situ 3D ED experiment in a gas environment and with it uncover the structure evolution of SrFeO2.5 as notably different from that reported from in situ X-ray and in situ neutron powder diffraction studies in gas environments. Using in situ 3D ED on submicron sized single crystals obtained from a high quality monodomain SrFeO2.5 single crystal , we observe the transformation under O2 flow of SrFeO2.5 with an intra- and interlayer ordering of the left and right twisted (FeO4) tetrahedral chains (space group Pcmb) into consecutively SrFeO2.75 with space group Cmmm (at 350°C, 33% O2) and SrFeO3-δ with space group Pm3 ̅m (at 400°C, 100% O2). Upon reduction in H2 flow, the crystals return to the brownmillerite structure with intralayer order, but without regaining the interlayer order of the pristine crystals. Therefore, redox cycling of SrFeO2.5 crystals in O2 and H2 introduces stacking faults into the structure, resulting in an I2/m(0βγ)0s symmetry with variable β.

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.

Abstract: Developing an efficient material as a counter electrode (CE) with excellent catalytic activity, intrinsic stability, and low cost is essential for the commercial application of dye-sensitized solar cells (DSSCs). Transition metal phosphides have been demonstrated as outstanding multifunctional catalysts in a broad range of energy conversion technologies. Here, we exploited different phases of iron phosphide as CEs in DSSCs with an I–/I3–-based electrolyte. Solvothermal synthesis using a triphenylphosphine precursor as a phosphorus source allows to grow a Fe2P phase at 300 °C and a FeP phase at 350 °C. The obtained iron phosphide catalysts were coated on fluorine-doped tin oxide substrates and heat-treated at 450 °C under an inert gas atmosphere. The solar-to-current conversion efficiency of the solar cells assembled with the Fe2P material reached 3.96 ± 0.06%, which is comparable to the device assembled with a platinum (Pt) CE. DFT calculations support the experimental observations and explain the fundamental origin behind the improved performance of Fe2P compared to FeP. These results indicate that the Fe2P catalyst exhibits excellent performance along with desired stability to be deployed as an efficient Pt-free alternative in DSSCs.