Abstract: We report a plasma‐assisted CO₂hydrogenation to CH₃OH over Fe₂O₃/γ‐Al₂O₃catalysts, achieving 12% CO₂conversion and 58% CH₃OH selectivity at a temperature of nearly 80°C atm pressure. We investigated the effect of various supports and loadings of the Fe‐based catalysts, as well as optimized reaction conditions. We characterized catalysts by X‐ray powder diffraction (XRD), hydrogen temperature programmed reduction (H₂‐TPR), CO₂and CO temperature programmed desorption (CO₂/CO‐TPD), high‐resolution transmission electron microscopy (HRTEM), scanning transmission electron microscopy (STEM), x‐ray photoelectron spectroscopy (XPS), Mössbauer, and Fourier transform infrared<bold>(</bold>FTIR). The XPS results show that the enhanced CO₂conversion and CH₃OH selectivity are attributed to the chemisorbed oxygen species on Fe₂O₃/γ‐Al₂O₃. Furthermore, the diffuse reflectance infrared Fourier transform spectroscopy (DRIFTs) and TPD results illustrate that the catalysts with stronger CO₂adsorption capacity exhibit a higher reaction performance.<italic>In situ</italic>DRIFTS gain insight into the specific reaction pathways in the CO₂/H₂plasma. This study reveals the role of chemisorbed oxygen species as a key intermediate, and inspires to design highly efficient catalysts and expand the catalytic systems for CO₂hydrogenation to CH₃OH.

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: technologies have been expanding, and one of the most exciting and rapidly growing
applications is in biology and medicine. Most biomedical studies with DBD plasma systems are performed in vitro, which include cells grown on the surface of plastic well plates, or in vivo, which include animal research models (e.g. mice, pigs). Since many DBD systems use the biological target as the secondary electrode for direct plasma generation and treatment, they are sensitive to the surface properties of the target, and thus can be altered based on the in vitro or in vivo system used. This could consequently affect biological response from plasma treatment. Therefore, in this study, we investigated the DBD plasma behavior both in vitro (i.e. 96-well flat bottom plates, 96-well U-bottom plates, and 24-well flat bottom plates), and in vivo (i.e. mouse skin). Intensified charge coupled device (ICCD) imaging was performed and the plasma discharges were visually distinguishable between the different systems. The geometry of the wells did not affect DBD plasma generation for low application distances (≤ 2 mm), but differentially affected plasma uniformity on the bottom of the well at greater distances. Since DBD plasma treatment in vitro is rarely performed in dry wells for plasma medicine experiments, the effect of well wetness was also investigated. In all in vitro cases, the uniformity of the DBD plasma was affected when comparing wet versus dry wells, with the plasma in the wide-bottom wells appearing the most similar to plasma generated on mouse skin. Interestingly, based on quantification of ICCD images, the DBD plasma intensity per surface area demonstrated an exponential one-phase decay with increasing application distance, regardless of the in vitro or in vivo system. This trend is similar to that of the energy per pulse of plasma, which is used to determine the total plasma treatment energy for biological systems. Optical emission spectroscopy performed on the plasma revealed similar trends in radical species generation between the plastic well plates and mouse skin. Therefore, taken together, DBD plasma intensity per surface area may be a valuable parameter to be used as a simple method for in situ monitoring during biological treatment and active plasma treatment control, which can be applied for in vitro and in vivo systems.

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: The effect of gas heating in laboratory sputter magnetrons is investigated by means of numerical modeling. The model is two-dimensional in the coordinate space and three-dimensional in the velocity space based on the particle-in-cellMonte Carlo collisions technique. It is expanded in a way that allows the inclusion of the neutral plasma particles (fast gas atoms and sputtered atoms), which makes it possible to calculate the gas temperature and its influence on the discharge behavior in a completely self-consistent way. The results of the model are compared to experimental measurements and to other existing simulation results. The results show that gas heating is pressure dependent (rising with the increase in the gas pressure) and should be taken into consideration at pressures above 10 mTorr.

Abstract: The influence of the composition on the crystallographic properties of deposited Mg(M)O (with M=Al, Cr, Ti, Y, and Zr) films is studied. For a flexible control of the composition, dual reactive magnetron sputtering was used as deposition technique. Two different approaches to predict the composition are discussed. The first is an experimental way based on the simple relationship between the deposition rate and the target-substrate distance. The second is a route using a Monte Carlo based particle trajectory code. Both methods require a minimal experimental input and enable the user to quickly predict the composition of complex thin films. Good control and flexibility allow us to study the compositional effects on the growth of Mg(M)O films. Pure MgO thin films were grown with a (111) preferential out-of-plane orientation. When adding M to MgO, two trends were noticed. The first trend is a change in the MgO lattice parameters compared to pure MgO. The second tendency is a decrease in the crystallinity of the MgO phase. The experimentally determined crystallographic properties are shown to be in correspondence with the predicted properties from molecular dynamics simulations.