Abstract: Atomistic simulation methods for the quantification of free energies are in wide use. These methods operate by sampling the probability density of a system along a small set of suitable collective variables (CVs), which is, in turn, expressed in the form of a free energy surface (FES). This definition of the FES can capture the relative stability of metastable states but not that of the transition state because the barrier height is not invariant to the choice of CVs. Free energy barriers therefore cannot be consistently computed from the FES. Here, we present a simple approach to calculate the gauge correction necessary to eliminate this inconsistency. Using our procedure, the standard FES as well as its gauge-corrected counterpart can be obtained by reweighing the same simulated trajectory at little additional cost. We apply the method to a number of systems—a particle solvated in a Lennard-Jones fluid, a Diels–Alder reaction, and crystallization of liquid sodium—to demonstrate its ability to produce consistent free energy barriers that correctly capture the kinetics of chemical or physical transformations, and discuss the additional demands it puts on the chosen CVs. Because the FES can be converged at relatively short (sub-ns) time scales, a free energy-based description of reaction kinetics is a particularly attractive option to study chemical processes at more expensive quantum mechanical levels of theory.

Abstract: Ammonia is an industrial large-volume chemical, with its main application in fertilizer production. It also attracts increasing attention as a green-energy vector. Over the past century, ammonia production has been dominated by the Haber-Bosch process, in which a mixture of nitrogen and hydrogen gas is converted to ammonia at high temperatures and pressures. Haber-Bosch processes with natural gas as the source of hydrogen are responsible for a significant share of the global CO(2)emissions. Processes involving plasma are currently being investigated as an alternative for decentralized ammonia production powered by renewable energy sources. In this work, we present the PNOCRA process (plasma nitrogen oxidation and catalytic reduction to ammonia), combining plasma-assisted nitrogen oxidation and lean NO(x)trap technology, adopted from diesel-engine exhaust gas aftertreatment technology. PNOCRA achieves an energy requirement of 4.6 MJ mol(-1)NH(3), which is more than four times less than the state-of-the-art plasma-enabled ammonia synthesis from N(2)and H(2)with reasonable yield (>1 %).

Abstract: We describe the plasma chemistry in a helium flowing atmospheric pressure afterglow (FAPA) used for analytical spectrometry, by means of a quasione-dimensional (1D) plasma chemical kinetics model. We study the effect of typical impurities present in the feed gas, as well as the afterglow in ambient humid air. The model provides the species density profiles in the discharge and afterglow regions and the chemical pathways. We demonstrate that H, N, and O atoms are formed in the discharge region, while the dominant reactive neutral species in the afterglow are O3 and NO. He* and He2* are responsible for Penning ionization of O2, N2, H2O, H2, and N, and especially O and H atoms. Besides, He2+ also contributes to ionization of N2, O2, H2O, and O through charge transfer reactions. From the pool of ions created in the discharge, NO+ and (H2O)3H+ are the dominant ions in the afterglow. Moreover, negatively charged clusters, such as NO3H2O− and NO2H2O−, are formed and their pathway is discussed as well. Our model predictions are in line with earlier observations in the literature about the important reagent ions and provide a comprehensive overview of the underlying pathways. The model explains in detail why helium provides a high analytical sensitivity because of high reagent ion formation by both Penning ionization and charge transfer. Such insights are very valuable for improving the analytical performance of this (and other) ambient desorption/ionization source(s).

Abstract: CO2 conversion by plasma technology is gaining increasing interest. We present a carbon (charcoal) bed placed after a Gliding Arc Plasmatron (GAP) reactor, to enhance the CO2 conversion, promote O/O2 removal and in­ crease the CO fraction in the exhaust mixture. By means of an innovative (silo) system, the carbon is constantly supplied, to avoid carbon depletion upon reaction with O/O2. Using this carbon bed, the CO2 conversion is enhanced by almost a factor of two (from 7.6 to 12.6%), while the CO concentration even increases by a factor of three (from 7.2 to 21.9%), and O2 is completely removed from the exhaust mixture. Moreover, the energy ef­ ficiency of the conversion process drastically increases from 27.9 to 45.4%, and the energy cost significantly drops from 41.9 to 25.4 kJ.L− 1. We also present the temperature as a function of distance from the reactor outlet, as well as the CO2, CO and O2 concentrations and the temperature in the carbon bed as a function of time, which is important for understanding the underlying mechanisms. Indeed, these time-resolved measurements reveal that the initial enhancements in CO2 conversion and in CO concentration are not maintained in our current setup. Therefore, we present a model to study the gasification of carbon with different feed gases (i.e., O2, CO and CO2 separately), from which we can conclude that the oxygen coverage at the surface plays a key role in determining the product composition and the rate of carbon consumption. Indeed, our model insights indicate that the drop in CO2 conversion and in CO concentration after a few minutes is attributed to deactivation of the carbon bed, due to rapid formation of oxygen complexes at the surface.

Abstract: Plasma-based NOx production is of interest for sustainable N2 fixation, but more research is needed to improve its performance. One of the current limitations is recombination of NO back into N2 and O2 molecules immediately after the plasma reactor. Therefore, we developed a novel so-called “effusion nozzle”, to improve the perfor­mance of a rotating gliding arc plasma reactor for NOx production, but the same principle can also be applied to other plasma types. Experiments in a wide range of applied power, gas flow rates and N2/O2 ratios demonstrate an enhancement in NOx concentration by about 8%, and a reduction in energy cost by 22.5%. In absolute terms, we obtain NOx concentrations up to 5.9%, at an energy cost down to 2.1 MJ/mol, which are the best values reported to date in literature. In addition, we developed four complementary models to describe the gas flow, plasma temperature and plasma chemistry, aiming to reveal why the effusion nozzle yields better performance. Our simulations reveal that the effusion nozzle acts as very efficient heat sink, causing a fast drop in gas tem­perature when the gas molecules leave the plasma, hence limiting the recombination of NO back into N2 and O2. This yields an overall higher NOx concentration than without the effusion nozzle. This immediate quenching right at the end of the plasma makes our effusion nozzle superior to more conventional cooling options, like water cooling In addition, this higher NOx concentration can be obtained at a slightly lower power, because the effusion nozzle allows for the ignition and sustainment of the plasma at somewhat lower power. Hence, this also explains the lower energy cost. Overall, our experimental results and detailed modeling analysis will be useful to improve plasma-based NOx production in other plasma reactors as well.

Abstract: Doping two single transition-metal (TM) atoms on a substrate host opens numerous possibilities for catalyst design. However, what if the substrate contains more than one vacancy site? Then, the combination of two TMs along with their distribution patterns becomes a design parameter potentially complementary to the substrate itself and the bimetal composition. In this study, we investigate ammonia synthesis under mild electrocatalytic conditions on a transition-metal-doped porous C24N24 catalyst using density functional theory (DFT). The TMs studied include Ti, Mn, and Cu in a 2:4 dopant ratio (Ti2Mn4@C24N24 and Ti2Cu4@N-24(24)). Our computations show that a single Ti atom in both catalysts exhibits the highest selectivity for N-2 fixation at ambient conditions. This work is a good theoretical model to establish the structure-activity relationship, and the knowledge earned from the metal-N-4 moieties may help studies of related nanomaterials, especially those with curved structures.

Abstract: We calculate bubble nucleation rates in a Lennard-Jones fluid through explicit molecular dynamics simulations. Our approach-based on a recent free energy method (dubbed reweighted Jarzynski sampling), transition state theory, and a simple recrossing correction-allows us to probe a fairly wide range of rates in several superheated and cavitation regimes in a consistent manner. Rate predictions from this approach bridge disparate independent literature studies on the same model system. As such, we find that rate predictions based on classical nucleation theory, direct brute force molecular dynamics simulations, and seeding are consistent with our approach and one another. Published rates derived from forward flux sampling simulations are, however, found to be outliers. This study serves two purposes: First, we validate the reliability of common modeling techniques and extrapolation approaches on a paradigmatic problem in materials science and chemical physics. Second, we further test our highly generic recipe for rate calculations, and establish its applicability to nucleation processes.

Abstract: We introduce a simple enhanced sampling approach for the calculation of free energy differences and barriers along a one-dimensional reaction coordinate. First, a small number of short nonequilibrium simulations are carried out along the reaction coordinate, and the Jarzynski equality is used to learn an approximate free energy surface from the nonequilibrium work distribution. This free energy estimate is represented in a compact form as an artificial neural network and used as an external bias potential to accelerate rare events in a subsequent molecular dynamics simulation. The final free energy estimate is then obtained by reweighting the equilibrium probability distribution of the reaction coordinate sampled under the influence of the external bias. We apply our reweighted Jarzynski sampling recipe to four processes of varying scales and complexities.spanning chemical reaction in the gas phase, pair association in solution, and droplet nucleation in supersaturated vapor. In all cases, we find reweighted Jarzynski sampling to be a very efficient strategy, resulting in rapid convergence of the free energy to high precision.

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: Binding of the SARS-CoV-2 S-glycoprotein to cell receptors is vital for the entry of the virus into cells and subsequent infection. ACE2 is the main cell receptor for SARS-CoV-2, which can attach to the C-terminal receptor-binding domain (RBD) of the SARS-CoV-2 S-glycoprotein. The GRP78 receptor plays an anchoring role, which attaches to the RBD and increases the chance of other RBDs binding to ACE2. Although high levels of reactive oxygen and nitrogen species (RONS) are produced during viral infections, it is not clear how they affect the RBD structure and its binding to ACE2 and GRP78. In this research, we apply molecular dynamics simulations to study the effect of oxidation of the highly reactive cysteine (Cys) amino acids of the RBD on its binding to ACE2 and GRP78. The interaction energy of both ACE2 and GRP78 with the whole RBD, as well as with the RBD main regions, is compared in both the native and oxidized RBDs. Our results show that the interaction energy between the oxidized RBD and ACE2 is strengthened by 155 kJ/mol, increasing the binding of the RBD to ACE2 after oxidation. In addition, the interaction energy between the RBD and GRP78 is slightly increased by 8 kJ/mol after oxidation, but this difference is not significant. Overall, these findings highlight the role of RONS in the binding of the SARS-CoV-2 S-glycoprotein to host cell receptors and suggest an alternative mechanism by which RONS could modulate the entrance of viral particles into the cells.

Abstract: Mixed hemi/ad-micelle sodium dodecyl sulfate (SDS)-coated magnetic iron oxide nanoparticles (MHAMS-MIONPs) were used as an efficient adsorbent for both removal and preconcentration of two important carcinogenic xanthine dyes named rhodamine-B (RB) and rhodamine-6G (RG). To gain insight in the configuration of SDS molecules on the surface of MIONPs, zeta potential measurements were performed in different [SDS]/[MIONP] ratios. Zeta potential data indicated that mixed hemi/ad-micelle MHAM was formed in [SDS]/[MIONP] ratios over the range of 1.1 to 7.3. Parameters affecting the adsorption of dyes were optimized as removal efficiency by one variable at-a-time and response surface methodology; the obtained removal efficiencies were ∼100%. Adsorption kinetic and equilibrium studies, under the optimum condition (pH = 2; amount of MIONPs = 87.15 mg; [SDS]/[MIONP] ratio = 2.9), showed that adsorption of both dyes are based on the pseudo-second-order and the Langmuir isotherm models, respectively. The maximum adsorption capacities for RB and RG were 385 and 323 mg g1, respectively. MHAMS-MIONPs were also applied for extraction of RB and RG. Under optimum conditions (pH = 2; amount of damped MHAMS-MIONPs = 90 mg; eluent solvent volume = 2.6 mL of 3% acetic acid in acetonitrile), extraction recoveries for 0.5 mg L1 of RB and RG were 98% and 99%, with preconcentration factors of 327 and 330, respectively. Limit of detection obtained for rhodamine dyes were <0.7 ng mL1. Finally, MHAMS-MIONPs were successfully applied for both removal and trace determination of RB and RG in environmental and wastewater samples.

Abstract: technologies have been expanding, and one of the most exciting and rapidly growing
applications is in biology and medicine. Most biomedical studies with DBD plasma systems are performed in vitro, which include cells grown on the surface of plastic well plates, or in vivo, which include animal research models (e.g. mice, pigs). Since many DBD systems use the biological target as the secondary electrode for direct plasma generation and treatment, they are sensitive to the surface properties of the target, and thus can be altered based on the in vitro or in vivo system used. This could consequently affect biological response from plasma treatment. Therefore, in this study, we investigated the DBD plasma behavior both in vitro (i.e. 96-well flat bottom plates, 96-well U-bottom plates, and 24-well flat bottom plates), and in vivo (i.e. mouse skin). Intensified charge coupled device (ICCD) imaging was performed and the plasma discharges were visually distinguishable between the different systems. The geometry of the wells did not affect DBD plasma generation for low application distances (≤ 2 mm), but differentially affected plasma uniformity on the bottom of the well at greater distances. Since DBD plasma treatment in vitro is rarely performed in dry wells for plasma medicine experiments, the effect of well wetness was also investigated. In all in vitro cases, the uniformity of the DBD plasma was affected when comparing wet versus dry wells, with the plasma in the wide-bottom wells appearing the most similar to plasma generated on mouse skin. Interestingly, based on quantification of ICCD images, the DBD plasma intensity per surface area demonstrated an exponential one-phase decay with increasing application distance, regardless of the in vitro or in vivo system. This trend is similar to that of the energy per pulse of plasma, which is used to determine the total plasma treatment energy for biological systems. Optical emission spectroscopy performed on the plasma revealed similar trends in radical species generation between the plastic well plates and mouse skin. Therefore, taken together, DBD plasma intensity per surface area may be a valuable parameter to be used as a simple method for in situ monitoring during biological treatment and active plasma treatment control, which can be applied for in vitro and in vivo systems.

Abstract: DBD plasma reactors are of great interest for environmental and energy applications, such as CO2 conversion, but they suffer from limited conversion and especially energy efficiency. The introduction of packing materials has been a popular subject of investigation in order to increase the reactor performance. Reducing the discharge gap of the reactor below one millimetre can enhance the plasma performance as well. In this work, we combine both effects and use a packed-bed DBD micro plasma reactor to investigate the influence of gap size reduction, in combination with a packing material, on the conversion and efficiency of CO2 dissociation. Packing materials used in this work were SiO2, ZrO2, and Al2O3 spheres as well as glass wool. The results are compared to a regular size reactor as a benchmark. Reducing the discharge gap can greatly increase the CO2 conversion, although at a lower energy efficiency. Adding a packing material further increases the conversion when keeping a constant residence time, but is greatly dependent on the material composition, gap and sphere size used. Maximum conversions of 50–55% are obtained for very long residence times (30 s and higher) in an empty reactor or with certain packing material combinations, suggesting a balance in CO2 dissociation and recombination reactions. The maximum energy efficiency achieved is 4.3%, but this is for the regular sized reactor at a short residence time (7.5 s). Electrical characterization is performed to reveal some trends in the electrical behaviour of the plasma upon reduction of the discharge gap and addition of a packing material.

Abstract: Plasma reactors are interesting for gas-based chemical conversion but the fundamental relation between the plasma chemistry and selected conditions remains poorly understood. Apparent kinetic parameters for the loss and formation processes of individual components of gas conversion processes, can however be extracted by performing experiments in an extended residence time range (2–75 s) and fitting the gas composition to a firstorder kinetic model of the evolution towards partial chemical equilibrium (PCE). We specifically investigated the differences in kinetic characteristics and PCE state of the CO2 dissociation and CH4 reforming reactions in a dielectric barrier discharge reactor (DBD), how these are mutually affected when combining both gases in the dry reforming of methane (DRM) reaction, and how they change when a packing material (non-porous SiO2) is added to the reactor. We find that CO2 dissociation is characterized by a comparatively high reaction rate of 0.120 s−1 compared to CH4 reforming at 0.041 s−1; whereas CH4 reforming reaches higher equilibrium conversions, 82% compared to 53.6% for CO2 dissociation. Combining both feed gases makes the DRM reaction to proceed at a relatively high rate (0.088 s−1), and high conversion (75.4%) compared to CO2 dissociation, through accessing new chemical pathways between the products of CO2 and CH4. The addition of the packing material can also distinctly influence the conversion rate and position of the equilibrium, but its precise effect depends strongly on the gas composition. Comparing different CO2:CH4 ratios reveals the delicate balance of the combined chemistry. CO2 drives the loss reactions in DRM, whereas CH4 in the mixture suppresses back reactions. As a result, our methodology provides some of the insight necessary to systematically tune the conversion process.

Abstract: Titanium dioxide (TiO2) is a unique material for biosensing applications due to its capability of hosting enzymes. For the first time, we show that TiO2 can accumulate reactive oxygen species (ROS) under daylight irradiation and can support the catalytic cycle of horseradish peroxidase (HRP) without the need of H2O2 to be present in the solution. Phenolic compounds, such as hydroquinone (HQ) and 4-aminophenol (4-AP), were detected amperometrically in flow-injection analysis (FIA) mode via the use of an electrode modified with TiO2 impregnated with HRP. In contrast to the conventional detection scheme, no H2O2 was added to the analyte solution. Basically, the inherited ability of TiO2 to generate reactive oxygen species is used as a strategy to avoid adding H2O2 in the solution during the detection of phenolic compounds. Electron paramagnetic resonance (EPR) spectroscopy indicates the presence of ROS on titania which, in interaction with HRP, initiate the electrocatalysis toward phenolic compounds. The amperometric response to 4-AP was linear in the concentration range between 0.05 and 2 μM. The sensitivity was 0.51 A M–1 cm–2, and the limit of detection (LOD) 26 nM. The proposed sensor design opens new opportunities for the detection of phenolic traces by HRP-based electrochemical biosensors, yet in a more straightforward and sensitive way following green chemistry principles of avoiding the use of reactive and harmful chemical, such as H2O2.