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: 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: Electrification and carbon capture technologies are essential for achieving net-zero emissions in the chemical sector. A crucial strategy involves converting captured CO2 into CO, a valuable chemical feedstock. This study evaluates the feasibility of two innovative methods: plasma activation and electrolysis, using clean electricity and captured CO2. Specifically, it compares a gliding arc plasma reactor with an embedded novel carbon bed system to a modern zero-gap type low-temperature electrolyser. The plasma method stood out with an energy cost of 19.5 GJ per tonne CO, marking a 43% reduction compared to electrolysis and conventional methods. CO production costs for plasma- and electrolysis-based plants were $671 and $962 per tonne, respectively. However, due to high uncertainty regarding electrolyser costs, the CO production costs in electrolysis-based plants may actually range from $570 to $1392 per tonne. The carbon bed system in the plasma method was a key factor in facilitating additional CO generation from O-2 and enhancing CO2 conversion, contributing to its cost-effectiveness. Challenges for electrolysis included high costs of equipment and low current densities. Addressing these limitations could significantly decrease production costs, but challenges arise from the mutual relationship between intrinsic parameters, such as CO2 conversion, CO2 input flow, or energy cost. In a future scenario with affordable feedstocks and equipment, costs could drop below $500 per tonne for both methods. While this may be more challenging for electrolysis due to complexity and expensive catalysts, plasma-based CO production appears more viable and competitive.

Abstract: Plasma medicine has attracted tremendous interest in a variety of medical conditions, ranging from wound healing to antimicrobial applications, even in cancer treatment, through the interactions of cold atmospheric plasma (CAP) and various biological tissues directly or indirectly. The underlying mechanisms of CAP treatment are still poorly understood although the oxidative effects of CAP with amino acids, peptides, and proteins have been explored experimentally. In this study, machine learning (ML) technology is introduced to efficiently unveil the interaction mechanisms of amino acids and reactive oxygen species (ROS) in seconds based on the data obtained from the reactive molecular dynamics (MD) simulations, which are performed to probe the interaction of five types of amino acids with various ROS on the timescale of hundreds of picoseconds but with the huge computational load of several days. The oxidative reactions typically start with H-abstraction, and the details of the breaking and formation of chemical bonds are revealed; the modification types, such as nitrosylation, hydroxylation, and carbonylation, can be observed. The dose effects of ROS are also investigated by varying the number of ROS in the simulation box, indicating agreement with the experimental observation. To overcome the limits of timescales and the size of molecular systems in reactive MD simulations, a deep neural network (DNN) with five hidden layers is constructed according to the reaction data and employed to predict the type of oxidative modification and the probability of occurrence only in seconds as the dose of ROS varies. The well-trained DNN can effectively and accurately predict the oxidative processes and productions, which greatly improves the computational efficiency by almost ten orders of magnitude compared with the reactive MD simulation. This study shows the great potential of ML technology to efficiently unveil the underpinning mechanisms in plasma medicine based on the data from reactive MD simulations or experimental measurements. In this study, since reactive molecular dynamics simulation can currently only describe interactions between a few hundred atoms in a few hundred picoseconds, deep neural networks (DNN) are introduced to enhance the simulation results by predicting more data efficiently. image

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: We have developed a comprehensive kinetic model to study the O atom kinetics in an O₂plasma and its afterglow. By adopting a pseudo-1D plug-flow formalism within the kinetic model, our aim is to assess how far the O atoms travel in the plasma afterglow, evaluating its potential as a source of O atoms for post-plasma gas conversion applications. Since we could not find experimental data for pure O₂plasma at atmospheric pressure, we first validated our model at low pressure (1–10 Torr) where very good experimental data are available. Good agreement between our model and experiments was achieved for the reduced electric field, gas temperature and the densities of the dominant neutral species, i.e. O₂(a), O₂(b) and O. Subsequently, we confirmed that the chemistry set is consistent with thermodynamic equilibrium calculations at atmospheric pressure. Finally, we investigated the O atom densities in the O₂plasma and its afterglow, for which we considered a microwave O₂plasma torch, operating at a pressure between 0.1 and 1 atm, for a flow rate of 20 slm and an specific energy input of 1656 kJ mol⁻¹. Our results show that for both pressure conditions, a high dissociation degree of ca. 92% is reached within the discharge. However, the O atoms travel much further in the plasma afterglow for<italic>p</italic>= 0.1 atm (9.7 cm) than for<italic>p</italic>= 1 atm (1.4 cm), attributed to the longer lifetime (3.8 ms at 0.1 atm vs 1.8 ms at 1 atm) resulting from slower three-body recombination kinetics, as well as a higher volumetric flow rate.

Abstract: The combination of plasma with catalysis for the synthesis and decomposition of NH3 is an attractive route to the production of carbon-neutral fertiliser and energy carriers and its conversion into H2. Recent years have seen fast developments in the field of plasma-catalytic NH3 life cycle. This work summarises the most recent advances in plasma-catalytic and related NH3-focussed processes, identifies some of the most important discoveries, and addresses plausible strategies for future developments in plasma-based NH3 technology.

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: Molecular dynamics simulations are essential for a better understanding of dissociative chemisorption on metal surfaces, which is often the rate-controlling step in heterogeneous and plasma catalysis. The workhorse quasi-classical trajectory approach ubiquitous in molecular dynamics is able to accurately predict reactivity only for high translational and low vibrational energies. In contrast, catalytically relevant conditions generally involve low translational and elevated vibrational energies. Existing quantum dynamics approaches are intractable or approximate as a result of the large number of degrees of freedom present in molecule−metal surface reactions. Here, we extend a ring polymer molecular dynamics approach to fully include, for the first time, the degrees of freedom of a moving metal surface. With this approach, experimental sticking probabilities for the dissociative chemisorption of methane on Pt(111) are reproduced for a large range of translational and vibrational energies by including nuclear quantum effects and employing full-dimensional simulations.

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.

Abstract: Non-equilibrium inductively coupled plasmas (ICPs) operating in hydrogen are of significant interest for applications including large-area materials processing. Increasing control of spatial gas heating, which drives the formation of neutral species density gradients and the rate of gas-temperature-dependent reactions, is critical. In this study, we use 2D fluid-kinetic simulations with the Hybrid Plasma Equipment Model to investigate the spatially resolved production of atomic hydrogen in a low-pressure planar ICP operating in pure hydrogen (10-20 Pa or 0.075-0.15 Torr, 300 W). The reaction set incorporates self-consistent calculation of the spatially resolved gas temperature and 14 vibrationally excited states. We find that the formation of neutral-gas density gradients, which result from spatially non-uniform electrical power deposition at constant pressure, can drive significant variations in the vibrational distribution function and density of atomic hydrogen when gas heating is spatially resolved. This highlights the significance of spatial gas heating on the production of reactive species in relatively high-power-density plasma processing sources.

Abstract: We explored the potential of plasma-based In-Situ Resource Utilization (ISRU) for Mars through the conversion of Martian atmosphere (~96% CO2, 2% N2, and 2% Ar) into life-sustaining chemicals. As the Martian surface pressure is about 1% of the Earth’s surface pressure, it is an ideal environment for plasma-based gas conversion using microwave reactors. At 1000 W and 10 Ln/min (normal liters per minute), we produced ~76 g/h of O2 and ~3 g/h of NOx using a 2.45 GHz waveguided reactor at 25 mbar, which is ~3.5 times Mars ambient pressure. The energy cost required to produce O2 was ~0.013 kWh/g, which is very promising compared to recently concluded MOXIE experiments on the Mars surface. This marks a crucial step towards realizing the extension of human exploration.

Abstract: Cold atmospheric plasma (CAP) is a source of cell‐damaging oxidant molecules that may be used as low‐cost cancer treatment with minimal side effects. Liquids treated with cold plasma and enriched with oxidants are a modality for non‐invasive treatment of internal tumors with cold plasma via injection. However, liquids are easily diluted with body fluids which impedes high and localized delivery of oxidants to the target. As an alternative, plasma‐treated hydrogels (PTH) emerge as vehicles for the precise delivery of oxidants. This study reports an optimal protocol for the preparation of injectable alginate PTH that ensures the preservation of plasma‐generated oxidants. The generation, storage, and release of oxidants from the PTH are assessed. The efficacy of the alginate PTH in cancer treatment is demonstrated in the context of cancer cell cytotoxicity and immunogenicity–release of danger signals and phagocytosis by immature dendritic cells, up to now unexplored for PTH. These are shown in osteosarcoma, a hard‐to‐treat cancer. The study aims to consolidate PTH as a novel cold plasma treatment modality for non‐invasive or postoperative tumor treatment. The results offer a rationale for further exploration of alginate‐based PTHs as a versatile platform in biomedical engineering.

Abstract: Ceramics and composites, many of whose physicochemical properties significantly exceed similar properties of metals and their alloys, are processed qualitatively mainly by the electroerosion method. Despite the existing works, the mechanism of the initial stage of the removal of materials has not yet been identified. For a comprehensive understanding of the mechanism of the removal of dielectrics, a new model is proposed based on the experimental results obtained on an improved electroerosion installation. It was revealed that the initial stage of the removal of a dielectric material consists of three successive stages that are associated with the synergistic effect on the process of the anionic group of electrolytes, plasma flare, and the cavitation shock. This makes it possible to better understand the mechanism of the removal of composite and ceramic materials, which should contribute to ensuring the machinability of those materials and their wide use in promising technologies.

Abstract: Herein, the efficacy of WOx-promoted CeO2-SiO2 and CeO2-ZrO2 mixed oxide catalysts in the solvent-free selective oxidation of benzyl alcohol to benzaldehyde using molecular oxygen as an oxidant is reported. We evaluated the effects of the oxidant and catalyst concentration, reaction duration, and temperature on the reaction with an aim to optimize the reaction conditions. The as-prepared CeO2, CeO2-ZrO2, CeO2-SiO2, WOx/CeO2, WOx/CeO2-ZrO2, and WOx/CeO2-SiO2 catalysts were characterized by X-ray diffraction (XRD), N-2 adsorption-desorption, Raman spectroscopy, temperature-programmed desorption of ammonia (TPD-NH3), X-ray photoelectron spectroscopy (XPS), and transmission electron microscopy (TEM). These characterisation results indicated that the WOx/CeO2-SiO2 catalyst possessed improved physicochemical (i.e., structural, textural, and acidic) properties owing to the strong interactivity between WOx and CeO2-SiO2. A higher number of Ce3+ ions (I-u '''/I-Total) were created with the WOx/CeO2-SiO2 catalyst than those with the other catalysts in this work, indicating the generation of a high number of oxygen vacancies. The WOx/CeO2-SiO2 catalyst exhibited a high conversion of benzyl alcohol (>99%) and a high selectivity (100%) toward benzaldehyde compared to the other promoted catalysts (i.e., WOx/CeO2 and WOx/CeO2-ZrO2), which is attributed to the smaller particle size of the WOx and CeO2 and their high specific surface area, more significant number of acidic sites, and superior number of oxygen vacancies. The WOx/CeO2-SiO2 catalyst could be quickly recovered and utilized at least five times without suffering any appreciable activity loss.