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 treatment of a well plate by an atmospheric pressure plasma jet is common for<italic>in vitro</italic>plasma medicine research. Here, reactive species are largely produced through the mixing of the jet effluent with the surrounding atmosphere. This mixing can be influenced not only by the ambient conditions, but also by the geometry of the treated well. To limit this influence and control the atmosphere, a shielding gas is sometimes applied. However, the interplay between the gas shield and the well geometry has not been investigated. In this work, we developed a 2D-axisymmetric computational fluid dynamics model of the kINPen plasma jet, to study the mixing of the jet effluent with the surrounding atmosphere, with and without gas shield. Our computational and experimental results show that the choice of well type can have a significant influence on the effluent conditions, as well as on the effectiveness of the gas shield. Furthermore, the geometry of the shielding gas device can substantially influence the mixing as well. Our results provide a deeper understanding of how the choice of setup geometry can influence the plasma treatment, even when all other operating parameters are unchanged.

Abstract: The use of microfluidic devices in the field of plasma-liquid interaction can unlock unique possibilities to investigate the effects of plasma-generated reactive species for environmental and biomedical applications. So far, very little simulation work has been performed on microfluidic devices in contact with a plasma source. We report on the modelling and computational simulation of physical and chemical processes taking place in a novel plasma-microfluidic platform. The main production and transport pathways of reactive species both in plasma and liquid are modelled by a novel modelling approach that combines 0D chemical kinetics and 2D transport mechanisms. This combined approach, applicable to systems where the transport of chemical species occurs in unidirectional flows at high Péclet numbers, decreases calculation times considerably compared to regular 2D simulations. It takes advantage of the low computational time of the 0D reaction models while providing spatial information through multiple plug-flow simulations to yield a quasi-2D model. The gas and liquid flow profiles are simulated entirely in 2D, together with the chemical reactions and transport of key chemical species. The model correctly predicts increased transport of hydrogen peroxide into the liquid when the microfluidic opening is placed inside the plasma effluent region, as opposed to inside the plasma region itself. Furthermore, the modelled hydrogen peroxide production and transport in the microfluidic liquid differs by less than 50% compared with experimental results. To explain this discrepancy, the limits of the 0D–2D combined approach are discussed.

Abstract: Warm plasma offers a promising route for CO2 splitting into valuable CO, yet recombination reactions of CO with oxygen, forming again CO2, have recently emerged as critical limitation. This study combines experiments and fluid dynamics + chemical kinetics modelling to comprehensively analyse the recombination reactions upon CO2 splitting in an atmospheric plasmatron. We introduce an innovative in-situ gas sampling technique, enabling 2D spatial mapping of gas product compositions and temperatures, experimentally confirming for the first time the substantial limiting effect of CO recombination reactions in the afterglow region. Our results show that the CO mole fraction at a 5 L/min flow rate drops significantly from 11.9 % at a vertical distance of z = 20 mm in the afterglow region to 8.6 % at z = 40 mm. We constructed a comprehensive 2D model that allows for spatial reaction rates analysis incorporating crucial reactions, and we validated it to kinetically elucidate this phenomenon. CO2 +M⇌O+CO+M and CO2 +O⇌CO+O2 are the dominant reactions, with the forward reactions prevailing in the plasma region and the backward reactions becoming prominent in the afterglow region. These results allow us to propose an afterglow quenching strategy for performance enhancement, which is further demonstrated through a meticulously developed plasmatron reactor with two-stage cooling. Our approach substantially increases the CO2 conversion (e.g., from 6.6 % to 19.5 % at 3 L/min flow rate) and energy efficiency (from 13.5 % to 28.5 %, again at 3 L/min) and significantly shortens the startup time (from ~ 150 s to 25 s). Our study underscores the critical role of inhibiting recombination reactions in plasma-based CO2 conversion and offers new avenues for performance enhancement.

Abstract: Plasma catalysis has emerged as a promising approach for driving thermodynamically unfavorable chemical
reactions. Nevertheless, comprehending the mechanisms involved remains a challenge, leading to uncertainty
about whether the optimal catalyst in plasma catalysis aligns with that in thermal catalysis. In this research, we
explore this question by studying monometallic catalysts (Fe, Co, Ni and Mo) and bimetallic catalysts (Fe-Co, Mo-
Co, Fe-Ni and Mo-Ni) in both thermal catalytic and plasma catalytic NH3 decomposition. Our findings reveal that
the Fe-Co bimetallic catalyst exhibits the highest activity in thermal catalysis, the Fe-Ni bimetallic catalyst
outperforms others in plasma catalysis, indicating a discrepancy between the optimal catalysts for the two
catalytic modes in NH3 decomposition. Comprehensive catalyst characterization, kinetic analysis, temperature
program surface reaction experiments and plasma diagnosis are employed to discuss the key factors influencing
NH3 decomposition performance.

Abstract: Microplasmas can be used for a wide range of technological applications and to improve the understanding of fundamental physics. Scanning electron microscopy, on the other hand, provides insights into the sample morphology and chemistry of materials from the mm‐ down to the nm‐scale. Combining both would provide direct insight into plasma‐sample interactions in real‐time and at high spatial resolution. Up till now, very few attempts in this direction have been made, and significant challenges remain. This work presents a stable direct current glow discharge microplasma setup built inside a scanning electron microscope. The experimental setup is capable of real‐time in situ imaging of the sample evolution during plasma operation and it demonstrates localized sputtering and sample oxidation. Further, the experimental parameters such as varying gas mixtures, electrode polarity, and field strength are explored and experimental<italic>V</italic>–<italic>I</italic>curves under various conditions are provided. These results demonstrate the capabilities of this setup in potential investigations of plasma physics, plasma‐surface interactions, and materials science and its practical applications. The presented setup shows the potential to have several technological applications, for example, to locally modify the sample surface (e.g., local oxidation and ion implantation for nanotechnology applications) on the µm‐scale.

Abstract: Plasma catalysis is a rapidly growing field, often employing a packed-bed dielectric barrier discharge plasma reactor. Such dielectric barrier discharges are complex, especially when a packing material (e.g., a catalyst) is introduced in the discharge volume. Catalysts are known to affect the plasma discharge, though the underlying mechanisms influencing the plasma physics are not fully understood. Moreover, the effect of the catalysts on the plasma discharge and its subsequent effect on the overall performance is often overlooked. In this work, we deliberately design and synthesize catalysts to affect the plasma discharge in different ways. These Ni or Co alumina-based catalysts are used in plasma-catalytic dry reforming of methane and ammonia synthesis. Our work shows that introducing a metal to the dielectric packing can affect the plasma discharge, and that the distribution of the metal is crucial in this regard. Further, the altered discharge can greatly influence the overall performance. In an atmospheric pressure dielectric barrier discharge reactor, this apparently more uniform plasma yields a significantly better performance for ammonia synthesis compared to the more conventional filamentary discharge, while it underperforms in dry reforming of methane. This study stresses the importance of analyzing the plasma discharge in plasma catalysis experiments. We hope this work encourages a more critical view on the plasma discharge characteristics when studying various catalysts in a plasma reactor.

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: Plasma‐based CO₂conversion has attracted increasing interest. However, to understand the impact of plasma operation on post‐plasma processes, we studied the effect of adding N₂, N₂/CH₄and N₂/CH₄/H₂O to a CO₂gliding arc plasmatron (GAP) to obtain valuable insights into their impact on exhaust stream composition and temperature, which will serve as feed gas and heat for post‐plasma catalysis (PPC). Adding N₂improves the CO₂conversion from 4 % to 13 %, and CH₄addition further promotes it to 44 %, and even to 61 % at lower gas flow rate (6 L/min), allowing a higher yield of CO and hydrogen for PPC. The addition of H₂O, however, reduces the CO₂conversion from 55 % to 22 %, but it also lowers the energy cost, from 5.8 to 3 kJ/L. Regarding the temperature at 4.9 cm post‐plasma, N₂addition increases the temperature, while the CO₂/CH₄ratio has no significant effect on temperature. We also calculated the temperature distribution with computational fluid dynamics simulations. The obtained temperature profiles (both experimental and calculated) show a decreasing trend with distance to the exhaust and provide insights in where to position a PPC bed.

Abstract: To support experimental research into gas conversion by warm plasmas, models should be developed to explain the experimental observations. These models need to describe all physical and chemical plasma properties in a coupled way. In this paper, we present a modelling approach to solve the complete set of assumed relevant equations, including gas flow, heat balance and species transport, coupled with a rather extensive chemistry set, consisting of 21 species, obtained by reduction of a more detailed chemistry set, consisting of 41 species. We apply this model to study the combined CO2 and CH4 conversion in the presence of O2, in a direct current atmospheric pressure glow discharge. Our model can predict the experimental trends, and can explain why higher O2 fractions result in higher CH4 conversion, namely due to the higher gas temperature, rather than just by additional chemical reactions. Indeed, our model predicts that when more O2 is added, the energy required to reach any set temperature (i.e., the enthalpy) drops, allowing the system to reach higher temperatures with similar amounts of energy. This is in turn related to the higher H2O fraction and lower H2 fraction formed in the plasma, as demonstrated by our model. Altogether, our new self-consistent model can capture the main physics and chemistry occurring in this warm plasma, which is an important step towards predictive modelling for plasma-based gas conversion.

Abstract: Nonthermal plasmas are currently being studied as a green alternative to the Haber-Bosch process, which is, today, the dominant industrial process allowing for the fixation of nitrogen and, as such, a fundamental component for the production of nitrogen-based industrial fertilizers. In this context, the gliding arc plasma (GAP) is considered a promising choice among nonthermal plasma options. However, its stability is still a key parameter to ensure industrial transfer of the technology. Nowadays, the conventional approach to stabilize this plasma process is to use external resistors. Although this indeed allows for an enhancement of the plasma stability, very little is reported about how it impacts the process efficiency, both in terms of NOx yield and energy cost. In this work, this question is specifically addressed by studying a DC-powered GAP utilized for nitrogen fixation into NOx at atmospheric pressure stabilized by variable external resistors. Both the performance and the stability of the plasma are reported as a function of the utilization of the resistors. The results confirm that while the use of a resistor indeed allows for a strong stabilization of the plasma without impacting the NOx yield, especially at high plasma current, it dramatically impacts the energy cost of the process, which increases from 2.82 to 7.9 MJ/mol. As an alternative approach, we demonstrate that the replacement of the resistor by an inductor is promising since it allows for decent stabilization of the plasma, while it does not affect either the energy cost of the process or the NOx yield.

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: Atmospheric pressure plasmas have shifted in recent years from being a burgeoning research field in the academic setting to an actively investigated technology in the chemical, oil, and environmental industries. This is largely driven by the climate change mitigation efforts, as well as the evident pathways of value creation by converting greenhouse gases (such as CO2) into useful chemical feedstock. Currently, most high technology readiness level (TRL) plasma-based technologies are based on volumetric and power-based scaling of thermal plasma systems, which results in large capital investment and regular maintenance costs. This work investigates bringing a quasi-thermal (so-called “warm”) plasma setup, namely, a gliding arc plasmatron, from a lab-scale to a pilot-scale capacity with an increase in throughput capacity by a factor of 10. The method of scaling is the parallelization of plasmatron reactors within a single housing, with the aim of maintaining a warm plasma regime while simultaneously improving build cost and efficiency (compared to separate reactors operating in parallel). Special attention is also given to the safety and control features implemented in the setup, a key component required for integration into industrial systems. The performance of the multi-reactor gliding arc plasmatron (MRGAP) reactor is investigated, focusing on the influence of flow rate and the number of active reactors. The location of active reactors was deemed to have a negligible effect on the monitored metrics of conversion, energy efficiency, and energy cost. The optimum operating conditions were found to be with the most active reactors (five) at the highest investigated flow rate (80 L/min). Analysis of results suggests that an optimum conversion (9%) and plug power-based energy efficiency (19%) can be maintained at a specific energy input (SEI) around 5.3 kJ/L (or 1 eV/molecule). The concept of parallelization of plasmatron reactors within a singular housing was demonstrated to be a viable method for scaling up from a lab-scale to a prototype-scale device, with performance analysis suggesting that increasing the power (through adding more reactor channels) and total flow rate, while maintaining an SEI around 5.3 or 4.2 kJ/L, i.e., 1.3 or 1 eV/molecule (based on plug power and plasma-deposited power, respectively), can result in increased conversion rate without sacrificing absolute conversion or energy efficiency.