Abstract: Herein, thin-layer potentiometry combined with ion-exchange membranes as barriers for charged interferences is demonstrated for the analytical detection of creatinine (CRE) in undiluted human urine. Briefly, CRE diffuses through an anion-exchange membrane (AEM) from a sample contained in one fluidic compartment to a second reservoir, containing the enzyme CRE deiminase. There, CRE reacts with the enzyme, and the formation of ammonium is dynamically monitored by potentiometric ammonium-selective electrodes. This analytical concept is integrated into a lab-on-a-chip microfluidic cell that allows for a high sample throughput and the operation under stop-flow mode, which allows CRE to passively diffuse across the AEM. Conveniently, positively charged species (i.e., potassium, sodium, and ammonium, among others) are repelled by the AEM and never reach the ammonium-selective electrodes; thus, possible interference in the response can be avoided. As a result, the dynamic potential response of the electrodes is entirely ascribed to the stoichiometric formation of ammonium. The new CRE biosensor exhibits a Nernstian slope, within a linear range of response from 1 to 50 mM CRE concentration. As expected, the response time (15–60 min) primarily depends on the CRE diffusion across the AEM. CRE analysis in urine samples displayed excellent results, without requiring sample pretreatment (before the introduction of the sample in the microfluidic chip) and with high compatibility with development into a potential point-of-care clinical tool. In an attempt to decrease the analysis time, the presented analytical methodology for CRE detection is translated into an all-solid-state platform, in which the enzyme is immobilized on the surface of the ammonium-selective electrode and with the AEM on top. While more work is necessary in this direction, the CRE sensor appears to be promising for CRE analysis in both urine and blood.

Abstract: The capability of energy-dispersive X-ray fluorescence was investigated for fast and simple chemical analysis of trace elements in sediments and particulate matter in sea water. Nuclepore 0.4 μm pore-size membranes are recommended as optimal filters for a straightforward collection of suspended material. The collection of suspended trace metals by filtration seemed to give a sufficiently homogeneous filter load (s% <2.5). Data are presented on the concentrations of K, Ca, Ti, Cr, Mn, Fe, Ni, Cu, Zn, Br, Pb, Rb and Sr with a fair precision (s% < 5.6) and accuracy.

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: Mannosylerythritol lipids (MELs) are a promising group of biosurfactants due to their high fermentation yield, selfassembly and biological activity. During fermentation by Pseudozyma aphidis, a mixture of MELs with different levels of acylation is formed, of which the fully deacetylated form is the most valuable. In order to reduce the environmental impact of deacetylation, an enzymatic process using natural deep eutectic solvents (NADES) has been developed. We tested the deacetylation of a purified MELs mixture with immobilized Candida antarctica lipase B enzyme and 2-ethylhexanol as co-substrate in 140 h reactions with different NADES. We identified hydrophobic NADES systems with similar yields and kinetics as in pure 2-ethylhexanol solvent. Our results indicate that deacetylation of MELs mixtures in NADES as a solvent is possible with yields comparable to pure co-substrate and that hydrophobic NADES without carboxylic acid compounds facilitate the reaction to the greatest extent.

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: Introducing defects in TiO2-based photocatalytic materials is a promising strategy for improving light-driven CO2 reduction. However, defects such as oxygen vacancies are generally unstable. As a solution and to further enhance the photocatalytic activity, metal doping has been applied. This mini review aims to summarize recent progress in this particular field. Herein, we have classified metal-doped architectures into three different categories: single metal doping, alloy- and co-doping, and doping of morphologically nanoengineered TiO2−x substrates. The direct relationship between specific metals and product selectivity remains complex, as selectivity can vary significantly among seemingly similar materials. However, numerous methods do show promise in fine-tuning selectivity towards either CO or CH4. In terms of photocatalytic turnover, remarkable yields have been reported in isolated reports, but insufficient experimental data and divergent reaction conditions hamper a true comparison. This puts an emphasis on the need for standardized activity testing.

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.