Abstract: Molecular dynamics simulations were used to investigate the size-dependent melting mechanism of nickel nanoclusters of various sizes. The melting process was monitored by the caloric curve, the overall cluster Lindemann index, and the atomic Lindemann index. Size-dependent melting temperatures were determined, and the correct linear dependence on inverse diameter was recovered. We found that the melting mechanism gradually changes from dynamic coexistence melting to surface melting with increasing cluster size. These findings are of importance in better understanding carbon nanotube growth by catalytic chemical vapor deposition as the phase state of the catalyst nanoparticle codetermines the growth mechanism.

Abstract: The CO and CO2 Dielectric Barrier Discharges (DBD) and their solid products were analyzed keeping similar energy input regimes. Gas chromatography analysis revealed the presence of CO2, CO and O-2 mixture in the exhaust of the CO2 DBD, while no O-2 was found when CO was used as a feed gas. It was shown that the C-2 Swan lines observed with optical emission spectroscopy were distinct in the CO plasma while they were not observed in the CO2 emission spectrum. Also the solid products of the plasmas exhibited remarkable differences. Nanoparticles with a diameter between10 and 300 nm, composed of Fe, O and C (Fe: O: C similar to 13: 50: 30) were produced by the CO2 DBD, while microscopic dendrite-like carbon structure (C: O similar to 73: 27) were formed in the CO plasma. The growth rate in the CO2 and CO DBDs was evaluated to be on the level of 0.15 mg/min and 15 mg/min, respectively. The difference of the CO and CO2 discharges and their products might be attributed to the oxygen content in the latter (6.4 mol.% O-2 in the exhaust) and subsequent etching of the carbonaceous film.

Abstract: The conversion of atmospheric nitrogen into valuable compounds, that is, so-called nitrogen fixation, is gaining increased interest, owing to the essential role in the nitrogen cycle of the biosphere. Plasma technology, and more specifically gliding arc plasma, has great potential in this area, but little is known about the underlying mechanisms. Therefore, we developed a detailed chemical kinetics model for a pulsed-power gliding-arc reactor operating at atmospheric pressure for nitrogen oxide synthesis. Experiments are performed to validate the model and reasonable agreement is reached between the calculated and measured NO and NO2 yields and the corresponding energy efficiency for NOx formation for different N2/O2 ratios, indicating that the model can provide a realistic picture of the plasma chemistry. Therefore, we can use the model to investigate the reaction pathways for the formation and loss of NOx. The results indicate that vibrational excitation of N2 in the gliding arc contributes significantly to activating the N2 molecules, and leads to an energy efficient way of NOx production, compared to the thermal process. Based on the underlying chemistry, the model allows us to propose solutions on how to further improve the NOx formation by gliding arc technology. Although the energy efficiency of the gliding-arc-based nitrogen fixation process at the present stage is not comparable to the world-scale Haber–Bosch process, we believe our study helps us to come up with more realistic scenarios of entering a cutting-edge innovation in new business cases for the decentralised production of fertilisers for agriculture, in which lowtemperature plasma technology might play an important role.

Abstract: This paper discusses the electrochemical behaviour of gelatin coated gold electrodes in physiological pH conditions in a potential window −1.5 till 1.0 V vs SCE by performing cyclic voltammetry. A comparison is made between gelatin A and gelatin B, which have respectively a positive and a negative net charge at physiological pH. The deposition of gelatin onto the gold surface is confirmed by means of attenuated total reflection-infrared (ATR-IR) spectroscopic analyses.

Abstract: Ammonia is a crucial nutrient used for plant growth and as a building block in pharmaceutical and chemical industry, produced via nitrogen fixation of the ubiquitous atmospheric N2. Current industrial ammonia production relies heavily on fossil resources, but a lot of work is put into developing non-fossil based pathways. Among these is the use of nonequilibrium plasma. In this work, we investigated water vapor as H source for nitrogen fixation into NH3 by non-equilibrium plasma. The highest selectivity towards NH3 was observed with low amounts of added H2O vapor, but the highest production rate was reached at high H2O vapor.

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: 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: Indoor environments are considered an important contributor to external human exposure to halogenated flame retardants (HFRs) due to the large amounts of chemicals currently incorporated in indoor equipment and the time humans spend every day in indoor environments. In this chapter, the presence and use of novel brominated flame retardants (NBFRs), dechlorane plus (DPs), chlorinated organophosphorus flame retardants (Cl-PFRs) and chlorinated paraffins (CPs) in indoor dust, air and consumer products collected from different indoor microenvironments (homes, public indoor spaces, and vehicles) are discussed. While data on the concentrations of HFRs in indoor dust and air are widely available, figures are still scarce for consumer products, such as textiles and foams, furnishings, flooring, electric and electronic products and building materials. This knowledge gaps still represents the biggest obstacle in linking eventual sources of contamination to the presence and chemical patterns in indoor dust and air.