Abstract: The Covid era has made us aware of the need for resilient, self-sufficient, and local production. We are likely willing to pay an extra price for that quality. Ammonia (NH3) synthesis accounts for 2 % of global energy production and is an important point of attention for the development of green energy technologies. Therefore, we propose a thermally integrated process for H2 production and NH3 synthesis using plasma technology, and we evaluate its techno-economic performance and CO2 footprint by life cycle assessment (LCA). The key is to integrate energy-wise a high-temperature plasma (HTP) process, with a (low-temperature) non-thermal plasma (NTP) process and to envision their joint economic potential. This particularly means raising the temperature of the NTP process, which is typically below 100 ◦ C, taking advantage of the heat released from the HTP process. For that purpose, we proposed the integrated process and conducted chemical kinetics simulations in the NTP section to determine the thermodynamically feasible operating window of this novel combined plasma process. The results suggest that an NH3 yield of 2.2 mol% can be attained at 302 ◦ C at an energy yield of 1.1 g NH3/kWh. Cost calculations show that the economic performance is far from commercial, mainly because of the too low energy yield of the NTP process. However, when we base our costs on the best literature value and plausible future scenarios for the NTP energy yield, we reach a cost prediction below 452 $/tonne NH3, which is competitive with conventional small-scale Haber-Bosch NH3 synthesis for distributed production. In addition, we demonstrate that biogas can be used as feed, thus allowing the proposed integrated reactor concept to be part of a biogas-to-ammonia circular concept. Moreover, by LCA we demonstrate the environmental benefits of the pro­posed plant, which could cut by half the carbon emissions when supplied by photovoltaic electricity, and even invert the carbon balance when supplied by wind power due to the avoided emissions of the carbon black credits.

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: 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: 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: The development of a stable, efficient and economic catalyst for hydrogen evolution reaction (HER) of water splitting is one of the most hopeful approaches to confront the environmental and energy crisis. A two-step method is employed to obtain metal clusters (Ru, N, Pd etc.) combining single cobalt atoms anchored on nitrogen-doped carbon (Ru/Pt/Pd@Co-SAs/N-C). Based on the synergistic effect between Ru clusters and single cobalt atoms, Ru@Co-SAs/N-C exhibits an outstanding HER electrocatalytic activity. Specifically, Ru@Co-SAs/N-C only needs 7 mV overpotential at 10 mA cm(-2) in 1 M KOH solution, which is much better than commercial 20 wt% PVC (40 mV) catalyst. Density functional theory (DFT) calculations further reveal the synergy effect between surface Ru nanoclusters and Co-SAs/N-C toward hydrogen adsorption for HER. Additionally, Ru@CoSAs/N-C also exhibits excellent catalytic ability and durability under acidic and neutral media. The present study opens a new avenue towards the design of metal clusters/single cobalt atoms heterostructures with outstanding performance toward HER and beyond.

Abstract: Highly monodispersed platinum-based nanoalloys are the best-known catalysts for the oxygen reduction reaction. Although certainly promising, the durability and stability are among the main requirements for commercializing fuel cell electrocatalysts in practical applications. Herein, we synthesize highly stable, durable and catalytic active monodispersed PtPd nano-particles encapsulated in a unique one particle@one cell structure by adjusting the viscosity of solvents using mesocellular foam. PtPd nanoparticles in mesocellular carbon foam exhibit an excellent electrocatalytic activity (over 4 times mass and specific activities than the commercial Pt/C catalyst). Most importantly, this nanocatalyst shows no obvious change of structure and only a 29.5% loss in electrochemically active surface area after 5000 potential sweeps between 0.6 and 1.1 V versus reversible hydrogen electrode cycles. (C) 2014 Elsevier Ltd. All rights reserved.

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 paper brings the comparison of performances of CO2 conversion by plasma and plasma-assisted catalysis based on the data collected from literature in this field, organised in an open access online data-base. This tool is open to all users to carry out their own analyses, but also to contributors who wish to add their data to the database in order to improve the relevance of the comparisons made, and ultimately to improve the efficiency of CO2 conversion by plasma-catalysis. The creation of this database and data-base user interface is motivated by the fact that plasma-catalysis is a fast-growing field for all CO2 con-version processes, be it methanation, dry reforming of methane, methanolisation, or others. As a result of this rapid increase, there is a need for a set of standard procedures to rigorously compare performances of different systems. However, this is currently not possible because the fundamental mechanisms of plasma-catalysis are still too poorly understood to define these standard procedures. Fortunately how-ever, the accumulated data within the CO2 plasma-catalysis community has become large enough to war-rant so-called “big data” studies more familiar in the fields of medicine and the social sciences. To enable comparisons between multiple data sets and make future research more effective, this work proposes the first database on CO2 conversion performances by plasma-catalysis open to the whole community. This database has been initiated in the framework of a H2020 European project and is called the “PIONEER DataBase”. The database gathers a large amount of CO2 conversion performance data such as conversion rate, energy efficiency, and selectivity for numerous plasma sources coupled with or without a catalyst. Each data set is associated with metadata describing the gas mixture, the plasma source, the nature of the catalyst, and the form of coupling with the plasma. Beyond the database itself, a data extraction tool with direct visualisation features or advanced filtering functionalities has been developed and is available online to the public. The simple and fast visualisation of the state of the art puts new results into context, identifies literal gaps in data, and consequently points towards promising research routes. More advanced data extraction illustrates the impact that the database can have in the understanding of plasma-catalyst coupling. Lessons learned from the review of a large amount of literature during the setup of the database lead to best practice advice to increase comparability between future CO2 plasma-catalytic studies. Finally, the community is strongly encouraged to contribute to the database not only to increase the visibility of their data but also the relevance of the comparisons allowed by this tool. (c) 2023 Science Press and Dalian Institute of Chemical Physics, Chinese Academy of Sciences. Published by ELSEVIER B.V. and Science Press. This is an open access article under the CC BY license (http://creati- vecommons.org/licenses/by/4.0/).

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: Over the past thirty years, European offshore wind farm development surged, yet end-of-life and decommissioning considerations were overshadowed by initial climate and energy security objectives during design and construction. As the first major projects near their final decade, numerous unanswered questions persist. Through a comprehensive literature review, this study identifies, maps, and evaluates challenges across technical, economic, environmental, social, and policy dimensions spanning five end-of-life phases: planning, dismantling, transport and logistics, waste management, and site recovery. Examining 42 publications reveals 46 distinct challenges affecting stakeholders such as the end-of-life supply chain, policy makers, and society. While 33% of the challenges manifested in the technical dimension, 48% of the challenges covered the planning phase. Notably, the economic challenge of vessel cost and availability was raised most often. Less-explored challenges underscore the importance of consideration before the end-of-life phase intensifies. The study illustrates the complex interconnection of numerous end-of-life challenges across phases, dimensions, and disciplines, emphasizing the imperative of addressing bottlenecks in a comprehensive and integrated manner. The results of this study help steering future research, while also improving awareness of challenges for stakeholders, emphasizing the need for collaborative efforts between governmental bodies and industry stakeholders to address imminent challenges through transparent guidelines, data exchange, and circular design principles. The novelty of this study lies in its holistic, multidisciplinary approach, systematic framework for identifying challenges, and critical perspective unveiling interconnectedness.

Abstract: The disordered phases of LiCB11H12 and NaCB11H12 possess superb superionic conductivities that make them suitable as solid electrolytes. In these materials, cation diffusion correlates with high orientational mobilities of the CB11H12- anions; however, the precise relationship has yet to be demonstrated. In this work, ab initio molecular dynamics and quasielastic neutron scattering are combined to probe anion reorientations and their mechanistic connection to cation mobility over a range of timescales and temperatures. It is found that anions do not rotate freely, but rather transition rapidly between orientations defined by the cation sublattice symmetry. The symmetry-breaking carbon atom in CB11H12- also plays a critical role by perturbing the energy landscape along the instantaneous orientation of the anion dipole, which couples fluctuations in the cation probability density directly to the anion motion. Anion reorientation rates exceed 3 x 10(10) s(-1), suggesting the underlying energy landscape fluctuates dynamically on diffusion-relevant timescales. Furthermore, carbon is found to modify the orientational preferences of the anions and aid rotational mobility, creating additional symmetry incompatibilities that inhibit ordering. The results suggest that synergy between the anion reorientational dynamics and the carbon-modified cation-anion interaction accounts for the higher ionic conductivity in CB11H12- salts compared with B12H122-.

Abstract: The combined use of clean technologies can lead amongst other benefits to reduced environmental impacts, improved system efficiencies, better management of land scarcity, and diminishment of the effect of power variability of intermittent clean energy sources. Nonetheless, private investors facing budgetary constraints will only opt to invest in the combination of technologies if the latter is more profitable than the investment in a single technology. The aim of the paper is to provide a systematic model for decision makers that allows them to evaluate the profitability of any random combination of technologies under budgetary constraints, and to compare this profitability with that of the individual projects in isolation. This research goes beyond the state of art in the field of financial management and more specifically in the field of the rationing of capital amongst interdependent projects, by developing a method to calculate the payoff of interdependent projects undertaken together. Moreover, this paper develops a computational model from the investor's point of view, of which the purpose is threefold: First, the model allows to directly compare the economic payoff of individual complementary technologies with the economic payoff of their integrated combination, under budgetary constraints. Second, the model calculates economic synergies labeled benefits of combined technologies' (BOCT) when combining complementary technologies. Third, the model explains the rationalization behind the presence of BOCT. The model exemplifies an ex ante cost benefit analysis developed for business and non-governmental use. A four step methodology is proposed and illustrated by means of a case study of PV solar power and battery electric vehicles (BEVs) for a small Belgian enterprise. Results show that at low electricity prices (<Euro0.112/kWh) it is most profitable to invest in BEVs. When the price of electricity rises (>Euro0.134/kWh), investment in exclusively PV becomes most attractive. In all other cases, it is more profitable to invest in the combination of both technologies. Copyright (c) 2015 John Wiley & Sons, Ltd.

Abstract: The main drawbacks of silicon as the most promising anode material for lithium-ion batteries (theoretical capacity=3572 mAh g−1) are lithiation-induced volume changes and the continuous formation of a solidelectrolyte interphase (SEI) upon cycling. A recent strategy is to focus on the influence of coatings and composite materials. To this end, the evolution of the SEI, as well as an applied carbon coating, on nanosilicon electrodes during the first electrochemical cycles is monitored. Two specific techniques are combined: Transmission Electron Microscopy (TEM) is used to study the surface evolution of the nanoparticles on a very local scale, whereas electrochemical impedance spectroscopy (EIS) provides information on the electrode level. A TEMEELS fingerprint signal of carbonate structures from the SEI is discovered, which can be used to differentiate between the SEI and a graphitic carbon matrix. Furthermore, the shielding effect of the carbon coating and the thickness evolution of the SEI are described.

Abstract: Controlling the morphology of organolead halide perovskite crystals is crucial to a fundamental understanding of the materials and to tune their properties for device applications. Here, we report a facile solution-based method for morphology-controlled synthesis of rod-like and plate-like organolead halide perovskite nanocrystals using binary capping agents. The morphology control is likely due to an interplay between surface binding kinetics of the two capping agents at different crystal facets. By high-resolution scanning transmission electron microscopy, we show that the obtained nanocrystals are monocrystalline. Moreover, long photoluminescence decay times of the nanocrystals indicate long charge diffusion lengths and low trap/defect densities. Our results pave the way for large-scale solution synthesis of organolead halide perovskite nanocrystals with controlled morphology for future device applications.

Abstract: The reduction of carbon dioxide (CO2) using porphyrin-containing 2D covalent organic frameworks (2D-COFs) catalysts is widely explored nowadays. While these framework materials are normally fabricated as powders followed by their uncontrolled surface heterogenization or directly grown as thin films (thickness >200 nm), very little is known about the performance of substrate-supported single-layered (approximate to 0.5 nm thickness) 2D-COFs films (s2D-COFs) due to its highly challenging synthesis and characterization protocols. In this work, a fast and straightforward fabrication method of porphyrin-containing s2D-COFs is demonstrated, which allows their extensive high-resolution visualization via scanning tunneling microscopy (STM) in liquid conditions with the support of STM simulations. The as-prepared single-layered film is then employed as a cathode for the electrochemical reduction of CO2. Fe porphyrin-containing s2D-COF@graphite used as a single-layered heterogeneous catalyst provided moderate-to-high carbon monoxide selectivity (82%) and partial CO current density (5.1 mA cm(-2)). This work establishes the value of using single-layered films as heterogene ous catalysts and demonstrates the possibility of achieving high performance in CO2 reduction even with extremely low catalyst loadings.