Abstract: As the field of perovskite optoelectronics developed, a plethora of strategies has arisen to control their electronic and morphological characteristics for the purpose of producing high efficiency devices. Unfortunately, despite this wealth of deposition approaches, the community experiences a great deal of irreproducibility between different laboratories, batches and preparation methods. Aiming to address this issue, we developed a simple deposition method based on gas quenching that yields smooth films for a wide range of perovskite compositions, in single, double, triple and quadruple cation varieties, and produces planar heterojunction devices with competitive efficiencies, so far up to 20%.

Abstract: Dissemination programs of nontraditional cookstoves often fail. Nontraditional cookstoves aim to solve problems associated with biomass fuel usage in developing countries. Recent studies do not explain what drives user's cookstove choice. This study therefore builds a holistic framework that centralizes product-specific preferences or needs. The case study identifies product-specific factors that influence rural Senegalese inhabitants to switch to solar cooking, using best worst scaling. Looking at the preferences, the case study classified 126 respondents, in three distinct market segments with different solar cooking expectations. The paper identifies socio-demographic characteristics that explain these differences in the respondents' preferences. Finally, the respondent sample is divided in two groups: solar cooker owners and non-owners. When studied with regard to the same issue, solar cooker owners appear to value benefits of the solar cooker lower than non-owners. This is due to program factors (such as formations, after-sales network) and miscommunication (such as a wrong image of the solar cooker) that highly influenced the respondents' cookstove choice. As a conclusion, solar cookers and solar cooking programs are not always adapted to the needs and requirements of the end-users. Needs-oriented and end-user adopted strategies are necessary in order to successfully implement nontraditional cookstoves programs. (C) 2013 Elsevier Ltd. All rights reserved.

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: 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: Three-dimensional (3D) computational fluid dynamics (CFD) simulations were performed to study solids flow dynamics and solids back-mixing behavior in a screw reactor (designed for thermal conversion of dry biomass particles) based on the Eulerian-Eulerian method. Simulation results were compared against experimental data with respect to filling degree and mean residence time of particles. The mean deviations for filling degree and for mean residence time between simulation and experiment were about 0.01 and 11.4 s, respectively, which shows that the model is reasonably accurate in predicting solids flow behavior in the screw reactor. The solids flow dynamics inside the reactor were discussed. The solids residence time distribution (RTD) was calculated and the degree of solids back-mixing in the forward transportation direction of the reactor was analyzed. It was found that solids being flung over the shaft and solids back-leakage, resulting from the low solids forward transportation velocity at the clearance between the flight and the bottom shell of the screw reactor, were responsible for solids back-mixing. The degree of solids back-mixing can be reduced at higher screw rotating speeds when keeping inlet mass flow rate of solids constant. (C) 2019 Elsevier Ltd. All rights reserved.

Abstract: Direct splitting of earth-abundant seawater provides an eco-friendly route for the production of clean H2, but is hampered by selectivity and stability issues. Direct seawater electrolysis is the most established technology, attaining high current densities in the order of 1–2 A cm−2. Alternatively, light-driven processes such as photocatalytic and photoelectrochemical seawater splitting are particularly promising as well, as they rely on renewable solar power. Solar-to-Hydrogen efficiencies have increased over the past decade from negligible values to about 2%. Especially the absence of large local pH changes (in the order of several tenths of a pH unit compared to up to 9 pH units for electrolysis) is a strong asset for pure photocatalysis. This may lead to less adverse side-reactions such as Cl2 and ClO− formation, (acid or base induced) corrosion and scaling. Besides, additional requirements for electrolytic cells, e.g. membranes and electricity input, are not needed in pure photocatalysis systems. In this review, the state-of-the-art technologies in light-driven seawater splitting are compared to electrochemical approaches with a focus on sustainability and stability. Promising advances are identified at the level of the catalyst as well as the process, and insight is provided in solutions crossing different fields.

Abstract: Biomass is expected to play an increasingly significant role in the greening of energy supply. Nevertheless, concerns are rising about the sustainability of large-scale energy crop production. Impacts must be assessed carefully before deciding whether and how this industry should be developed, and what technologies, policies and investment strategies should be pursued. There is need for a comprehensive and reliable sustainability assessment tool to evaluate the environmental, social and economic performance of biomass energy production. This paper paves the way for such a tool by analysing and comparing the performance and applicability of a selection of existing tools that are potentially useful for sustainability assessment of bioenergy systems. The selected tools are: Criteria And Indicators (C&I), Life Cycle Assessment (LCA), Environmental Impact Assessment (EIA), Cost Benefit Analysis (CBA), Exergy Analysis (EA) and System Perturbation Analysis (SPA). To evaluate the tools, a framework was constructed that consists of four evaluation levels: sustainability issues, tool attributes, model structure, area of application. The tools were then evaluated using literature data and with the help of a Delphi panel of experts. Finally, a statistical analysis was performed on the resulting data matrix to detect significant differences between tools. It becomes clear that none of the selected tools is able to perform a comprehensive sustainability assessment of bioenergy systems. Every tool has its particular advantages and disadvantages, which means that trade-offs are inevitable and a balance must be found between scientific accuracy and pragmatic decision making. A good definition of the assessment objective is therefore crucial. It seems an interesting option to create a toolbox that combines procedural parts of C&I and EIA, supplemented with calculation algorithms of LCA and CBA for respectively environmental and economic sustainability indicators. Nevertheless, this would require a more comprehensive interdisciplinary approach to align the different tool characteristics and focuses.

Abstract: The need for carbon negative technologies led to the development of a wide array of novel CO₂conversion techniques. Most of them either rely on high temperatures or generate highly reactive O species, which can lead to the undesirable formation of NO_xand N₂O when the CO₂feeds contain N₂. Here, we show that, for plasma-based CO₂conversion, adding a hydrogen source, as a chemical oxygen scavenger, can suppress their formation,<italic>in situ</italic>. This allows the use of low-cost N₂containing (industrial and direct air capture) feeds, rather than expensive purified CO₂. To demonstrate this, we add CH₄to a dielectric barrier discharge plasma used for converting impure CO₂. We find that when adding a stoichiometric amount of CH₄, 82% less NO₂and 51% less NO are formed. An even higher reduction (96 and 63%) can be obtained when doubling this amount. However, in that case the excess radicals promote the formation of by-products, such as HCN, NH₃and CH₃OH. Thus, we believe that by using an appropriate amount of chemical scavengers, we can use impure CO₂feeds, which would bring us closer to ‘real world’ conditions and implementation.

Abstract: The use of plasma technology for CO2 splitting is gaining increasing interest, but one of the major obstacles to date for industrial implementation is the considerable energy cost. We demonstrate that the introduction of a packing of dielectric zirconia (ZrO2) beads into a dielectric barrier discharge (DBD) plasma reactor can enhance the CO2 conversion and energy efficiency up to a factor 1.9 and 2.2, respectively, compared to that in a normal (unpacked) DBD reactor. We obtained a maximum conversion of 42 % and a maximum energy efficiency of 9.6 %. However, it is the ability of the packing to almost double both the conversion and the energy efficiency simultaneously at certain input parameters that makes it very promising. The improved conversion and energy efficiency can be explained by the higher values of the local electric field and electron energy near the contact points of the beads and the lower breakdown voltage, demonstrated by 2 D fluid modeling.

Abstract: Plasma technology is gaining increasing interest for gas conversion applications, such as CO2 conversion into value-added chemicals or renewable fuels, and N2 fixation from the air, to be used for the production of small building blocks for, e.g., mineral fertilizers. Plasma is generated by electric power and can easily be switched on/off, making it, in principle, suitable for using intermittent renewable electricity. In this Perspective article, we explain why plasma might be promising for this application. We briefly present the most common types of plasma reactors with their characteristic features, illustrating why some plasma types exhibit better energy efficiency than others. We also highlight current research in the fields of CO2 conversion (including the combined conversion of CO2 with CH4, H2O, or H2) as well as N2 fixation (for NH3 or NOx synthesis). Finally, we discuss the major limitations and steps to be taken for further improvement.

Abstract: Research in plasma reactor designs is developing rapidly as plasma technology is gaining increasing interest for sustainable gas conversion applications, like the conversion of greenhouse gases into value-added chemicals and renewable fuels, and fixation of N₂from air into precursors of mineral fertilizer. As plasma is generated by electric power and can easily be switched on/off, these applications allows for efficient conversion and energy storage of intermittent renewable electricity. In this paper, we present a new comprehensive modelling approach for the design and development of gliding arc plasma reactors, which reveals the fluid dynamics, the arc behaviour and the plasma chemistry by solving a unique combination of five complementary models. This results in a complete description of the plasma process, which allows one to efficiently evaluate the performance of a reactor and indicate possible design improvements before actually building it. We demonstrate the capabilities of this method for an experimentally validated study of plasma-based NO_xformation in a rotating gliding arc reactor, which is gaining increasing interest as a flexible, electricity-driven alternative for the Haber–Bosch process. The model demonstrates the importance of the vortex flow and the presence of a recirculation zone in the reactor, as well as the formation of hot spots in the plasma near the cathode pin and the anode wall that are responsible for most of the NO_xformation. The model also reveals the underlying plasma chemistry and the vibrational non-equilibrium that exists due to the fast cooling during each arc rotation. Good agreement with experimental measurements on the studied reactor design proves the predictive capabilities of our modelling approach.

Abstract: Upgrading ethane with CO2 as a soft oxidant represents a desirable means of obtaining oxygenated hydrocarbons. This reaction is not thermodynamically feasible under mild conditions and has not been previously achieved as a one-step process. Nonthermal plasma was implemented as an alternative means of supplying energy to overcome activation barriers, leading to the production of alcohols, aldehydes, and acids as well as C1−C5+ hydrocarbons under ambient pressure, with a maximum total oxygenate selectivity of 12%. A plasma chemical kinetic computational model was developed and found to be in good agreement with the experimental trends. Results from this study illustrate the potential to use plasma for the direct synthesis of value-added alcohols, acids, and aldehydes from ethane and CO2 under mild conditions.

Abstract: Plasma-catalytic ammonia decomposition as a method for producing hydrogen was studied in a packed-bed dielectric barrier discharge (DBD) reactor at ambient pressure and a fixed plasma power. The influence of packing the plasma zone with various dielectric materials, typically used as catalyst supports, was examined. At conditions (21 W, 75 Nml/min NH3) where an NH3 conversion of 5% was achieved with plasma alone, an improved decomposition was found when introducing dielectric materials with dielectric constants between 4 and 30. Of the tested materials, MgAl2O4 yielded the highest conversion (15.1%). The particle size (0.3-1.4 mm) of the MgAl2O4 packing was found to have a modest influence on the conversion, which dropped from 15.1% to 12.6% with increasing particle size. Impregnation of MgAl2O4 with different metals was found to decrease the NH3 conversion, with the Ni impregnation still showing an improved conversion (7%) compared to plasma-only. The plasma-assisted ammonia decomposition occurs in the gas phase due to micro-discharges, as evident from a linear correlation between the conversion and the frequency of micro-discharges for both plasma alone and with the various solid packing materials. The primary function of the solid is thus to facilitate the gas phase reaction by assisting the creation of micro-discharges. Lastly, insulation of the reactor to raise the temperature to 230 degrees C in the plasma zone was found to have a negative effect on the conversion, as a change from volume discharges to surface discharges occurred. The study shows that NH3 can be decomposed to provide hydrogen by exposure to a non-thermal plasma, but further developments are needed for it to become an energy efficient technology. (C)2022 The Author(s). Published by Elsevier Ltd on behalf of Hydrogen Energy Publications LLC.

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/).