Abstract: In traditional capacitively coupled plasmas, the discharge can be described by an electrostatic model, in which the Poisson equation is employed to determine the electrostatic electric field. However, current plasma reactors are much larger and driven at a much higher frequency. If the excitation wavelength k in the plasma becomes comparable to the electrode radius, and the plasma skin depth d becomes comparable to the electrode spacing, the electromagnetic (EM) effects will become significant and compromise the plasma uniformity. In this regime, capacitive discharges have to be described by an EM model, i.e., the full set of Maxwells equations should be solved to address the EM effects. This paper gives an overview of the theory, simulation and experiments that have recently been carried out to understand these effects, which cause major uniformity problems in plasma processing for microelectronics and flat panel display industries. Furthermore, some methods for improving the plasma uniformity are also described and compared.

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: Plasma-based gas conversion has great potential for enabling carbon-free fertilizer production powered by renewable electricity. Sustaining an energy-efficient plasma process without eroding the containment vessel is currently a significant challenge, limiting scaling to higher powers and throughputs. Isolation of the plasma from contact with any solid surfaces is an advantage, which both limits energy loss to the walls and prevents material erosion that could lead to disastrous soil contamination. This paper presents highly energy-efficient nitrogen fixation from air into NOx by microwave plasma, with the plasma filament isolated at the center of a quartz tube using a vortex gas flow. NOx production is found to scale very efficiently when increasing both gas flow rate and absorbed power. The lowest energy cost recorded of ~2 MJ/mol, for a total NOx production of ~3.8%, is the lowest reported up to now for atmospheric pressure plasmas.

Abstract: e investigate atmospheric pressure microwave (MW) plasma (2.45 GHz) conversion in CO2 and CH4 mixtures (i.e., dry reforming of methane, DRM) focusing on reaction performance and carbon formation. Promising energy costs of ~2.8–3.0 eV/molecule or ~11.1–11.9 kJ/L are amongst the best performance to date considering the current state-of-the-art for plasma-based DRM for all types of plasma. The conversion is in the range of ~46–49% and ~55–67% for CO2 and CH4, respectively, producing primarily syngas (i.e., H2 and CO) with H2/CO ratios of ~0.6–1 at CH4 fractions ranging from 30% to 45%. Water is the largest byproduct with levels ranging ~7–14% in the exhaust. Carbon particles visibly impact the plasma at higher CH4 fractions (> 30%), where they become heated and incandescent. Particle luminosity increases with increasing CH4 fractions, with the plasma becoming unstable near a 1:1 mixture (i.e., > 45% CH4). Electron microscopy of the carbon material reveals an agglomerated morphology of pure carbon nanoparticles. The mean particle size is determined as ~20 nm, free of any metal contamination, consistent with the electrode-less MW design.

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 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: Cold atmospheric plasma and nanomedicine originally emerged as individual domains, but are increasingly applied in combination with each other. Most research is performed in the context of cancer treatment, with only little focus yet on the possible synergies. Many questions remain on the potential of this promising hybrid technology, particularly regarding regenerative medicine and tissue engineering. In this perspective article, we therefore start from the fundamental mechanisms in the individual technologies, in order to envision possible synergies for wound healing and tissue recovery, as well as research strategies to discover and optimize them. Among these strategies, we demonstrate how cold plasmas and nanomaterials can enhance each other’s strengths and overcome each other’s limitations. The parallels with cancer research, biotechnology and plasma surface modification further serve as inspiration for the envisioned synergies in tissue regeneration. The discovery and optimization of synergies may also be realized based on a profound understanding of the underlying redox- and field-related biological processes. Finally, we emphasize the toxicity concerns in plasma and nanomedicine, which may be partly remediated by their combination, but also partly amplified. A widespread use of standardized protocols and materials is therefore strongly recommended, to ensure both a fast and safe clinical implementation.

Abstract: Controlling and steering the growth of single walled carbon nanotubes is often believed to require controlling of the nucleation stage. Yet, little is known about the microscopic mechanisms governing the nucleation from hydrocarbon molecules. Specifically, we address here the dehydrogenation of hydrocarbon molecules and the formation of all-carbon graphitic islands on metallic nanoclusters from hydrocarbon molecules under conditions typical for carbon nanotube growth. Employing reactive molecular dynamics simulations, we demonstrate for the first time that the formation of a graphitic network occurs through the intermediate formation of vertically oriented, not fully dehydrogenated graphitic islands. Upon dehydrogenation of these vertical graphenes, the islands curve over the surface, thereby forming a carbon network covering the nanoparticle. The results indicate that controlling the extent of dehydrogenation offers an additional parameter to control the nucleation of carbon nanotubes.

Abstract: Using reactive molecular dynamics simulations, the melting behavior of nickelcarbon nanoclusters is examined. The phase diagrams of icosahedral and Wulff polyhedron clusters are determined using both the Lindemann index and the potential energy. Formulae are derived for calculating the equilibrium constants and the solid and liquid fractions during a phase transition, allowing more rational determination of the melting temperature with respect to the arbitrary Lindemann value. These results give more insight into the properties of nickelcarbon nanoclusters in general and can specifically be very useful for a better understanding of the synthesis of carbon nanotubes using the catalytic chemical vapor deposition method.

Abstract: Unlocking the enormous technological potential of carbon nanotubes strongly depends on our ability to specifically produce metallic or semiconducting tubes. While selective etching of both has already been demonstrated, the underlying reasons, however, remain elusive as yet. We here present computational and experimental evidence on the operative mechanisms at the atomic scale. We demonstrate that during the adsorption of H atoms and their coalescence, the adsorbed ortho hydrogen pairs on single-walled carbon nanotubes induce higher shear stresses than axial stresses, leading to the elongation of HC–CH bonds as a function of their alignment with the tube chirality vector, which we denote as the γ-angle. As a result, the C–C cleavage occurs more rapidly in nanotubes containing ortho H-pairs with a small γ-angle. This phenomenon can explain the selective etching of small-diameter semiconductor nanotubes with a similar curvature. Both theoretical and experimental results strongly indicate the important role of the γ-angle in the selective etching mechanisms of carbon nanotubes, in addition to the nanotube curvature and metallicity effects and lead us to clearly understand the onset of selective synthesis/removal of CNT-based materials.

Abstract: In recent years there has been growing interest in the use of low-temperature atmospheric pressure plasmas for biomedical applications. Currently, however, there is very little fundamental knowledge regarding the relevant interaction mechanisms of plasma species with living cells. In this paper, we investigate the interaction of important plasma species, such as O3, O2 and O atoms, with bacterial peptidoglycan (or murein) by means of reactive molecular dynamics simulations. Specifically, we use the peptidoglycan structure to model the gram-positive bacterium Staphylococcus aureus murein. Peptidoglycan is the outer protective barrier in bacteria and can therefore interact directly with plasma species. Our results demonstrate that among the species mentioned above, O3 molecules and especially O atoms can break important bonds of the peptidoglycan structure (i.e. CO, CN and CC bonds), which subsequently leads to the destruction of the bacterial cell wall. This study is important for gaining a fundamental insight into the chemical damaging mechanisms of the bacterial peptidoglycan structure on the atomic scale.

Abstract: In this paper we study two cold atmospheric pressure plasma jets, operating in Ar + 2% air, with a different electrode geometry but with the same power dissipated in the plasma. The density profiles of the biomedically active NO and O species throughout the plasma jet, previously obtained by laser diagnostics, are calculated by means of a zero-dimensional semi-empirical reaction kinetics model. A good agreement between the calculated and measured data is demonstrated. Furthermore, the most probable spatial power distribution in an RF driven plasma jet is obtained for the first time by comparing measured and calculated species density profiles. This was possible due to the strong effect of the power distribution on the NO and O density profiles. In addition the dominant reaction pathways for both the NO and the O species are identified. The model allows us to obtain key information on the reactive species production inside the jet, which is difficult to access by laser diagnostics in a coaxial geometry. Finally, we demonstrate that water impurities in the order of 100 ppm in the gas feed can have a significant effect on the spatial distribution of the NO and O density.