Abstract: A gliding arc plasmatron (GAP), which is very promising for purification and gas conversion,
is characterized in nitrogen using optical emission spectroscopy and high-speed photography,
because the cross sections of electron impact excitation of N 2 are well known. The gas
temperature (of about 5500 K), the electron density (up to 1.5 × 10 15 cm −3 ) and the reduced
electric field (of about 37 Td) are determined using an absolutely calibrated intensified charge-
coupled device (ICCD) camera, equipped with an in-house made optical arrangement for
simultaneous two-wavelength diagnostics, adapted to the transient behavior of a GA channel
in turbulent gas flow. The intensities of nitrogen molecular emission bands, N 2 (C–B,0–0) as
well as N +
2 (B–X,0–0), are measured simultaneously. The electron density and the reduced
electric field are determined at a spatial resolution of 30 µm, using numerical simulation and
measured emission intensities, applying the Abel inversion of the ICCD images. The temporal
behavior of the GA plasma channel and the formation of plasma plumes are studied using a
high-speed camera. Based on the determined plasma parameters, we suggest that the plasma
plume formation is due to the magnetization of electrons in the plasma channel of the GAP by
an axial magnetic field in the plasma vortex.

Abstract: Dielectric barrier discharges (DBDs) typically operate in the filamentary regime and thus exhibit great spatial and temporal non-uniformity. In order to optimize DBDs for various applications, such as in plasma catalysis, more fundamental insight is needed. Here, we consider how the millions of microdischarges, characteristic for a DBD, influence individual gas molecules. We use a Monte Carlo approach to determine the number of microdischarges to which a single molecule would be exposed, by means of particle tracing simulations through a full-scale packed bed DBD reactor, as well as an empty DBD reactor. We find that the fraction of microdischarges to which the molecules are exposed can be approximated as the microdischarge volume over the entire reactor gas volume. The use of this concept provides good agreement between a plasma-catalytic kinetics model and experiments for plasma-catalytic NH3 synthesis. We also show that the concept of the fraction of microdischarges indicates the efficiency by which the plasma power is transferred to the gas molecules. This generalised concept is also applicable for other spatially and temporally non-uniform plasmas.

Abstract: Packed bed dielectric barrier discharge (PB-DBD) plasma reactors are very promising for various plasma catalysis applications, but the exact mechanisms of plasma-catalyst interaction are far from understood, because the plasma discharge and catalyst/packing properties are mutually dependent. To better understand the effect of packing dielectric material on the electrical plasma properties, we study here a single bead DBD plasma reactor operating in dry air, with beads of different dielectric constant and for different applied voltages, by means of fluid modelling validated by optical imaging experiments. Our study reveals that the plasma in the single bead DBD reactor can manifest itself in two different modalities, i.e. (a) polar discharges at the bead poles in contact with the electrodes, and (b) a streamer discharge caused by surface ionization waves, which bridges the gas gap. Beads with high dielectric constant result in localised electric field enhancement and hence yield a reduction of the applied voltage required for plasma production. At low applied voltage, the discharge appears as polar discharges between the bead and the electrodes, and upon higher voltage it undergoes a transition into a bridging streamer discharge. The transition voltage to the streamer mode rises for beads with higher dielectric constant. These observations are important for plasma catalysis applications. A higher dielectric constant yields a higher electric field and thus higher average electron energy and density, giving rise to more reactive species, but it also yields a confined discharge near the contact points of packing beads, limiting the interaction area between the catalyst and the active plasma species. In addition, our model reveals that the dielectric bead behaves as a capacitor and traps charges, which can explain the significant occurrence of partial discharging in PB-DBDs and non-parallelogram shaped Lissajous plots. Hence, equivalent circuit modelling of PB-DBDs should take into account the role of packing beads in charge trapping as a capacitor.

Abstract: Computer simulations are performed for an argon inductively coupled plasma (ICP) with a capacitive radio-frequency bias power, to investigate the bias effect on the discharge mode transition and on the plasma characteristics at various ICP currents, bias voltages, and bias frequencies. When the bias frequency is fixed at 13.56 MHz and the ICP current is low, e.g., 6A, the spatiotemporal averaged plasma density increases monotonically with bias voltage, and the bias effect is already prominent at a bias voltage of 90 V. The maximum of the ionization rate moves toward the bottom electrode, which indicates clearly the discharge mode transition in inductive/capacitive discharges. At higher ICP currents, i.e., 11 and 13 A, the plasma density decreases first and then increases with bias voltage, due to the competing mechanisms between the ion acceleration power dissipation and the capacitive power deposition. At 11 A, the bias effect is still important, but it is noticeable only at higher bias voltages. At 13 A, the ionization rate is characterized by a maximum at the reactor center near the dielectric window at all selected bias voltages, which indicates that the ICP power, instead of the bias power, plays a dominant role under this condition, and no mode transition is observed. Indeed, the ratio of the bias power to the total power is lower than 0.4 over a wide range of bias voltages, i.e., 0300V. Besides the effect of ICP current, also the effect of various bias frequencies is investigated. It is found that the modulation of the bias power to the spatiotemporal distributions of the ionization rate at 2MHz is strikingly different from the behavior observed at higher bias frequencies. Furthermore, the minimum of the plasma density appears at different bias voltages, i.e., 120V at 2MHz and 90V at 27.12 MHz.

Abstract: A two-dimensional hybrid Monte Carlofluid model, incorporating a full-wave solution of Maxwell's equations, is employed to describe the behavior of high frequency (HF) and very high frequency capacitively coupled plasmas (CCPs), operating both at single frequency (SF) and dual frequency (DF) in a CF4/O2 gas mixture. First, the authors investigate the plasma composition, and the simulations reveal that besides CF4 and O2, also COF2, CF3, and CO2 are important neutral species, and CF+3 and F− are the most important positive and negative ions. Second, by comparing the results of the model with and without taking into account the electromagnetic effects for a SF CCP, it is clear that the electromagnetic effects are important, both at 27 and 60 MHz, because they affect the absolute values of the calculation results and also (to some extent) the spatial profiles, which accordingly affects the uniformity in plasma processing. In order to improve the plasma radial uniformity, which is important for the etch process, a low frequency (LF) source is added to the discharge. Therefore, in the major part of the paper, the plasma uniformity is investigated for both SF and DF CCPs, operating at a HF of 27 and 60 MHz and a LF of 2 MHz. For this purpose, the authors measure the etch rates as a function of position on the wafer in a wide range of LF powers, and the authors compare them with the calculated fluxes toward the wafer of the plasma species playing a role in the etch process, to explain the trends in the measured etch rate profiles. It is found that at a HF of 60 MHz, the uniformity of the etch rate is effectively improved by adding a LF power of 2 MHz and 300 W, while its absolute value increases by about 50%, thus a high etch rate with a uniform distribution is observed under this condition.

Abstract: Density functional theory is widely used to gain insights into molecule−metal surface reaction networks, which is important for a better understanding of catalysis. However, it is well-known that generalized gradient approximation (GGA)
density functionals (DFs), most often used for the study of reaction networks, struggle to correctly describe both gas-phase molecules and metal surfaces. Also, GGA DFs typically underestimate reaction barriers due to an underestimation of the selfinteraction energy. Screened hybrid GGA DFs have been shown to reduce this problem but are currently intractable for wide usage. In this work, we use a more affordable meta-GGA (mGGA) DF in combination with a nonlocal correlation DF for the first time to study and gain new insights into a catalytically important surface
reaction network, namely, CO2 hydrogenation on Cu. We show that the mGGA DF used, namely, rMS-RPBEl-rVV10, outperforms typical GGA DFs by providing similar or better predictions for metals and molecules, as well as molecule−metal surface adsorption
and activation energies. Hence, it is a better choice for constructing molecule−metal surface reaction networks.

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.