Abstract: In a circular economy (CE), materials, components and products should be kept at the highest level of functionality, while phenomena like dilution, mixing and contamination, often referred to as the loss of resources, should be avoided. One method that can assess the performance of systems to concentrate or avoid dilution of resources is Statistical Entropy Analysis (SEA). Up till now, the method has been applied on the substance level (elements and compounds) only, but showed its applicability to various scales and a variety of systems. Further development of the method allowed to consider information on the product, component and material levels, which makes the method applicable to different combinations of CE strategies, both destructive (e.g. recycling) and non-destructive (e.g. reuse). The method is demonstrated on a simplified vehicle life-cycle, which is modeled through four component groups and six materials. It shows that the method allows to evaluate different CE strategies and identify critical stages which lead to the most severe resource and functionality losses. Based on the methods results, it is possible to determine a perfect circularity reference level, representing a system state that preserves functionality and avoids resource losses. The introduction of a circularity reference level enables the establishment of a framework for resource effectiveness in which diluting and concentrating effects of activities (e.g. sorting) are quantified. The distance of a system to an ideal circular state determines the deviation from a resource-effective system that maintains the original product functionality over a maximum period of time, with minimal efforts.

Abstract: Our economy drives on reactive nitrogen (Nr); while Nr emissions to the environment surpass the planetary boundary. Increasingly, it is advocated to recover Nr contained in waste streams and to reuse it ‘directly’ in the agri-food chain. Alternatively, Nr in waste streams may be removed as N2 and refixed via the Haber-Bosch process in an ‘indirect’ reuse loop. As a systematic sustainability analysis of ‘direct’ Nr reuse and its comparison to the ‘indirect’ reuse loop is lacking, this structured review aimed to analyze literature determining the environmental and economic sustainability of Nr recovery technologies. Bibliometric records were queried from 2000 to 2020 using Boolean search strings, and manual text coding. In total, 63 studies were selected for the review. Results suggest that ‘direct’ Nr reuse using Nr recovery technologies is the preferred paradigm as the majority of studies concluded that it is sustainable or that it can be sustainable depending on technological assumptions and other scenario variables. Only 17 studies compared the ‘direct’ with the ‘indirect’ Nr reuse route, therefore a system perspective in Nr recovery sustainability assessments should be more widely adopted. Furthermore, Nr reuse should also be analyzed in the context of a ‘new Nr economy’ that relies on decentralized Nr production from renewable energy. It is also recommended that on-par technology readiness level comparisons should be carried out, making use of technology development and technology learning methodologies. Finally, by-products of Nr recovery are important to be accounted for as they are reducing the environmental burdens through avoided impacts.

Abstract: The COVID-19 pandemic had large repercussions for our economy and organizations. Improved resilience can give organizations the ability to withstand crises and build back better and faster. This article assesses resilience of organizations and sole proprietorships in the context of the COVID-19 pandemic with eight circular strategies as explanatory variables. Furthermore, these eight circular strategies are also used to assess the organizations' and sole proprietorships' resilience outside of the COVID-19 pandemic. This analysis is conducted to explain how circular strategies can help companies and sole proprietorships maintain stability. The analysis was performed by means of a survey conducted between May and June 2020 in Flanders (Belgium), using a sample of 542 respondents. After performing a regression analysis combined with expert opinions collected through interviews, we find that companies and sole proprietorships with a higher circularity score have a significantly higher resilience score during crises and during normal times, compared to less circular companies. Furthermore, we find that the size of the company does not matter during a crisis to adapt and react flexibly, while it is important when there is no crisis. Finally, we argue that it is the combination of different circular strategies which yields to the highest results for the organizations' resilience and we provide policy recommendations based on the most asked support measures.

Abstract: The objective of this paper is to examine the recycling rates for mechanical and thermochemical recycling of postconsumer polyethylene flexible packaging after the implementation of different policy instruments. The study uses a supply chain equilibrium model that incorporates market data and techno-economic assessments to simulate market equilibrium. It combines this with a life cycle assessment to explore the environmental implications of implementing different policy instruments. The results show that instruments that do not target a specific technology are more likely to increase thermochemical recycling than mechanical recycling. Furthermore, a higher recycling rate is not equivalent to a better environmental outcome. An increased collection target that ensures a supply of plastic waste would increase the overall recycling rates the most. A recycled content standard for mechanical recycling would lead to the highest increase in mechanical recycling, with top results for environmental indicators, but low results for economic indicators.

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: The use of high amounts of iridium in industrial proton exchange membrane water electrolysers (PEMWE) could hinder their widespread use for the decarbonisation of society with hydrogen. Non-thermally oxidised Ir nanoparticles supported on antimony-doped tin oxide (SnO2:Sb, ATO) aerogel allow decreasing the use of the precious metal by more than 70 %, while enhancing the electro-catalytic activity and stability. To date the origin of these benefits remains unknown. Here we present clear evidence on the mechanisms that lead to the enhancement of the electrochemical properties of the catalyst. Operando near ambient pressure X-ray photoelectron spectroscopy on membrane electrode assemblies reveals a low degree of Ir oxidation, attributed to the oxygen spill-over from Ir to SnO2:Sb. Furthermore, the formation of highly unstable Ir(III) species is mitigated, while the decrease of Ir dissolution in Ir/SnO2:Sb is confirmed by inductively coupled plasma mass spectrometry (ICP-MS). The mechanisms that lead to the high activity and stability of Ir catalyst supported on SnO2:Sb aerogel for PEMWE are thus unveiled.

Abstract: Bimetallic nanoparticles with tailored size and specific composition have shown promise as stable and selective catalysts for electrochemical reduction of CO2 (CO2R) in batch systems. Yet, limited effort was devoted to understand the effect of ligand coverage and postsynthesis treatments on CO2 reduction, especially under industrially applicable conditions, such as at high currents (>100 mA/cm2) using gas diffusion electrodes (GDE) and flow reactors. In this work, Cu–Ag core–shell nanoparticles (11 ± 2 nm) were prepared with three different surface modes: (i) capped with oleylamine, (ii) capped with monoisopropylamine, and (iii) surfactant free with a reducing borohydride agent; Cu–Ag (OAm), Cu–Ag (MIPA), and Cu–Ag (NaBH4), respectively. The ligand exchange and removal was evidenced by infrared spectroscopy (ATR-FTIR) analysis, whereas high-resolution scanning transmission electron microscopy (HAADF-STEM) showed their effect on the interparticle distance and nanoparticle rearrangement. Later on, we developed a process-on-substrate method to track these effects on CO2R. Cu–Ag (OAm) gave a lower on-set potential for hydrocarbon production, whereas Cu–Ag (MIPA) and Cu–Ag (NaBH4) promoted syngas production. The electrochemical impedance and surface area analysis on the well-controlled electrodes showed gradual increases in the electrical conductivity and active surface area after each surface treatment. We found that the increasing amount of the triple phase boundaries (the meeting point for the electron–electrolyte–CO2 reactant) affect the required electrode potential and eventually the C+2e̅/C2e̅ product ratio. This study highlights the importance of the electron transfer to those active sites affected by the capping agents—particularly on larger substrates that are crucial for their industrial application.

Abstract: Although recent studies have advanced the understanding of pyrolyzed
Fe−N−C materials as oxygen reduction reaction (ORR) catalysts, the atomic and
electronic structures of the active sites and their detailed reaction mechanisms still remain unknown. Here, based on first-principles density functional theory (DFT) computations, we discuss the electronic structures of three FeN4 catalytic centers with different local topologies of the surrounding C atoms with a focus on unraveling the mechanism of their ORR activity in acidic electrolytes. Our study brings back a forgotten, synthesized pyridinic Fe−N coordinate to the community’s attention, demonstrating that this catalyst can exhibit excellent activity for promoting direct four-electron ORR through the addition of a fifth ligand such as −NH2, −OH, and −SO4. We also identify sites with good stability properties through the combined use of our DFT calculations and Mössbauer spectroscopy data.

Abstract: Bimetallic electrocatalysts have emerged as a viable strategy to tune the electrocatalytic CO2 reduction reaction (eCO2RR) for the selective production of valuable base chemicals and fuels. However, obtaining high product selectivity and catalyst stability remain challenging, which hinders the practical application of eCO2RR. In this work, it was found that a small doping concentration of tin (Sn) in copper oxide (CuO) has profound influence on the catalytic performance, boosting the Faradaic efficiency (FE) up to 98% for carbon monoxide (CO) at -0.75 V versus RHE, with prolonged stable performance (FE > 90%) for up to 15 h. Through a combination of ex situ and in situ characterization techniques, the in situ activation and reaction mechanism of the electrocatalyst at work was elucidated. In situ Raman spectroscopy measurements revealed that the binding energy of the crucial adsorbed *CO intermediate was lowered through Sn doping, thereby favoring gaseous CO desorption. This observation was confirmed by density functional theory, which further indicated that hydrogen adsorption and subsequent hydrogen evolution were hampered on the Sn-doped electrocatalysts, resulting in boosted CO formation. It was found that the pristine electrocatalysts consisted of CuO nanoparticles decorated with SnO2 domains, as characterized by ex situ high-resolution scanning transmission electron microscopy and X-ray photoelectron spectroscopy measurements. These pristine nanoparticles were subsequently in situ converted into a catalytically active bimetallic Sn-doped Cu phase. Our work sheds light on the intimate relationship between the bimetallic structure and catalytic behavior, resulting in stable and selective oxide-derived Sn-doped Cu electrocatalysts.

Abstract: Resource recovery from source-separated urine can shorten nutrient cycles on Earth and is essential in regenerative life support systems for deep-space exploration. In this study, a robust two-stage, energy-efficient, gravity-independent urine treatment system was developed to transform fresh real human urine into a stable nutrient solution. In the first stage, up to 85% of the COD was removed in a microbial electrolysis cell (MEC), converting part of the energy in organic compounds (27-46%) into hydrogen gas and enabling full nitrogen recovery by preventing nitrogen losses through denitrification in the second stage. Besides COD removal, all urea was hydrolysed in the MEC, resulting in a stream rich in ammoniacal nitrogen and alkalinity, and low in COD. This stream was fed into a membrane-aerated biofilm reactor (MABR) in order to convert the volatile and toxic ammoniacal nitrogen to non-volatile nitrate by nitrification. Bio-electrochemical pre-treatment allowed to recover all nitrogen as nitrate in the MABR at a bulk-phase dissolved oxygen level below 0.1 mg O2 L-1. In contrast, feeding the MABR directly with raw urine (omitting the first stage), at the same nitrogen loading rate, resulted in nitrogen loss (18%) due to denitrification. The MEC and MABR were characterised by very distinct and diverse microbial communities. While (strictly) anaerobic genera, such as Geobacter (electroactive bacteria), Thiopseudomonas, a Lentimicrobiaceae member, Alcaligenes and Proteiniphilum prevailed in the MEC, the MABR was dominated by aerobic genera, including Nitrosomonas (a known ammonium oxidiser), Moheibacter and Gordonia. The two-stage approach yielded a stable nitrate-rich, COD-low nutrient solution, suitable for plant and microalgae cultivation.

Abstract: Livestock production is utilizing large amounts of protein-rich feed ingredients such as soybean meal. The proven negative environmental impacts of soybean meal production incentivize the search for alternative protein sources. One promising alternative is Microbial Protein (MP), i.e. dried microbial biomass. To date, only few life cycle assessments (LCAs) for MP have been carried out, none of which has used a consequential modelling approach nor has been investigating the production of MP on food and beverage wastewater. Therefore, the objective of this study is to evaluate the environmental impact of MP production on a food and beverage effluent as a substitute for soybean meal using a consequential modelling approach. Three different types of MP production were analysed, namely consortia containing Aerobic Heterotrophic Bacteria (AHB), Microalgae and AHB (MaB), and Purple Non-Sulfur Bacteria (PNSB). The production of MP was modelled for high-strength potato wastewater (COD = 10 kg/m3) at a flow rate of 1,000 m3/day. LCA results were compared against soybean meal production for the endpoint impact categories human health, ecosystems, and resources. Soybean meal showed up to 52% higher impact on human health and up to 87% higher impact on ecosystems than MP. However, energy-related aspects resulted in an 8–88% higher resource exploitation for MP. A comparison between the MP production systems showed that MaB performed best when considering ecosystems (between 13 and 14% better) and resource (between 71 and 80% better) impact categories, while AHB and PNSB had lower values for the impact category human health (8–12%). The sensitivity analysis suggests that the conclusions drawn are robust as in the majority of 1,000 Monte Carlo runs the initial results are confirmed. In conclusion, it is suggested that MP is an alternative protein source of comparatively low environmental impact that should play a role in the future protein transition, in particular when further process improvements can be implemented and more renewable or waste energy sources will be used.

Abstract: The appearance of massless Dirac fermions in graphene requires two equivalent carbon sublattices of trigonal shape. While the generation of an effective mass and a band gap at the Dirac point remains an unresolved problem for freestanding extended graphene, it is well established by breaking translational symmetry by confinement and by breaking sublattice symmetry by interaction with a substrate. One of the strongest sublattice-symmetry-breaking interactions with predicted and measured band gaps ranging from 400 meV to more than 3 eV has been attributed to the interfaces of graphene with Ni and Co, which are also promising spin-filter interfaces. Here, we apply angle-resolved photoemission to epitaxial graphene on Ni (111) and Co(0001) to show the presence of intact Dirac cones 2.8 eV below the Fermi level. Our results challenge the common belief that the breaking of sublattice symmetry by a substrate and the opening of the band gap at the Dirac energy are in a straightforward relation. A simple effective model of a biased bilayer structure composed of graphene and a sublattice-symmetry-broken layer, corroborated by density-functional-theory calculations, demonstrates the general validity of our conclusions.

Abstract: Here, we show a novel solidsolidvapor (SSV) growth mechanism whereby epitaxial growth of heterogeneous semiconductor nanowires takes place by evaporation-induced cation exchange. During heating of PbSe-CdSe nanodumbbells inside a transmission electron microscope (TEM), we observed that PbSe nanocrystals grew epitaxially at the expense of CdSe nanodomains driven by evaporation of Cd. Analysis of atomic-resolution TEM observations and detailed atomistic simulations reveals that the growth process is mediated by vacancies.