Abstract: Natural deep eutectic solvents (NADES) are mixtures of naturally derived compounds with a significantly decreased melting point due to the specific interactions among the constituents. NADES have benign properties (low volatility, flammability, toxicity, cost) and tailorable physicochemical properties (by altering the type and molar ratio of constituents), hence they are often considered as a green alternative to common organic solvents. Modeling the relation between their composition and properties is crucial though, both for understanding and predicting their behavior. Several efforts were done to this end, yet this review aims at structuring the present knowledge as an outline for future research. First, we reviewed the key properties of NADES and relate them to their structure based on the available experimental data. Second, we reviewed available modeling methods applicable to NADES. At the molecular level, density functional theory and molecular dynamics allow interpreting density differences and vibrational spectra, and computation of interaction energies. Additionally, properties at the level of the bulk media can be explained and predicted by semi-empirical methods based on ab initio methods (COSMO-RS) and equation of state models (PC-SAFT). Finally, methods based on large datasets are discussed; models based on group contribution methods and machine learning. A combination of bulk media and dataset modeling allows qualitative prediction and interpretation of phase equilibria properties on the one hand, and quantitative prediction of melting point, density, viscosity, surface tension and refractive indices on the other hand. In our view, multiscale modeling, combining the molecular and macroscale methods, will strongly enhance the predictability of NADES properties and their interaction with solutes, yielding truly tailorable solvents to accommodate (bio)chemical reactions.

Abstract: Plasmonic catalysis in the colloidal phase requires robust surface ligands that prevent particles from aggregation in adverse chemical environments and allow carrier flow from reagents to nanoparticles. This work describes the use of a water-soluble conjugated polymer comprising a thiophene moiety as a surface ligand for gold nanoparticles to create a hybrid system that, under the action of visible light, drives the conversion of the biorelevant NAD+ to its highly energetic reduced form NADH. A combination of advanced microscopy techniques and numerical simulations revealed that the robust metal-polymer heterojunction, rich in sulfonate functional groups, directs the interaction of electron-donor molecules with the plasmonic photocatalyst. The tight binding of polymer to the gold surface precludes the need for conventional transition-metal surface cocatalysts, which were previously shown to be essential for photocatalytic NAD(+) reduction but are known to hinder the optical properties of plasmonic nanocrystals. Moreover, computational studies indicated that the coating polymer fosters a closer interaction between the sacrificial electron-donor triethanolamine and the nanoparticles, thus enhancing the reactivity.

Abstract: The effects of inaccurate sample sizes and sample positioning on 14 MeV neutron activation analysis results are estimated for 30, 20 and 10 mm diameter targets. It appears that axial positioning is the most critical parameter and that using a larger tritium target will yield an overall improvement of the reproducibility.

Abstract: We present here data of mineral dust variability retrieved from an ice core of the central West Antarctic, spanning the last five decades. Main evidence provided by the geochemical analysis is that northerly air mass incursions to the coring site, tracked by insoluble dust microparticles, have declined over the past 50 yr. This result contrasts with dust records from ice cores reported to the coastal West Antarctic that show increases since mid-20th century. We attribute this difference to regional climatic changes due to the ozone depletion and its implications to westerly winds. We found that the diameters of insoluble microparticles in the central West Antarctica ice core are significantly correlated with cyclone depth (energy) and wind intensity around Antarctica.

Abstract: An innovative experimental approach to study the electrodeposition of small nanoparticles and the early stages of electrochemical nucleation and growth is presented. Carbon coated gold TEM grids are used as substrates for the electrodeposition of silver nanoparticles so that electrochemical data, FESEM, HAADFSTEM and HRTEM data can be acquired from the same sample without the need to remove the particles from the substrate. It is shown that the real distribution of nanoparticles cannot be resolved by FESEM whereas HAADFSTEM analysis confirms that a distribution of small nanoparticles (d ≈ 12 nm) coexist with large nanoparticles corresponding to a bimodal size distribution. Besides, particles grown under the same conditions have been found to present different structures such as monocrystals, polycrystals or aggregates of smaller particles.

Abstract: There is currently a growing interest in the realisation and optimization of hybrid plasma/catalyst systems for a multitude of applications, ranging from nanotechnology to environmental chemistry. In spite of this interest, there is, however, a lack in fundamental understanding of the underlying processes in such systems. While a lot of experimental research is already being carried out to gain this understanding, only recently the first simulations have appeared in the literature. In this contribution, an overview is presented on atomic scale simulations of plasma catalytic processes as carried out in our group. In particular, this contribution focusses on plasma-assisted catalyzed carbon nanostructure growth, and plasma catalysis for greenhouse gas conversion. Attention is paid to what can routinely be done, and where challenges persist.

Abstract: Theoretical studies on molecule-metal surface reactions have so far been limited to small surface unit cells due to computational costs. Here, for the first time molecular dynamics simulations on very large surface unit cells at the level of density functional theory are performed, allowing a direct comparison to experiments performed on a curved crystal. Specifically, the reaction of D-2 on a curved Pt crystal is investigated with a neural network potential (NNP). The developed NNP is also accurate for surface unit cells considerably larger than those that have been included in the training data, allowing dynamical simulations on very large surface unit cells that otherwise would have been intractable. Important and complex aspects of the reaction mechanism are discovered such as diffusion and a shadow effect of the step. Furthermore, conclusions from simulations on smaller surface unit cells cannot always be transfered to larger surface unit cells, limiting the applicability of theoretical studies of smaller surface unit cells to heterogeneous catalysts with small defect densities.

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: The hyperdynamics method is a powerful tool to simulate slow processes at the atomic level. However, the construction of an optimal hyperdynamics potential is a task that is far from trivial. Here, we propose a generally applicable implementation of the hyperdynamics algorithm, borrowing two concepts from metadynamics. First, the use of a collective variable (CV) to represent the accelerated dynamics gives the method a very large flexibility and simplicity. Second, a metadynamics procedure can be used to construct a suitable history-dependent bias potential on-the-fly, effectively turning the algorithm into a self-learning accelerated molecular dynamics method. This collective variable-driven hyperdynamics (CVHD) method has a modular design: both the local system properties on which the bias is based, as well as the characteristics of the biasing method itself, can be chosen to match the needs of the considered system. As a result, system-specific details are abstracted from the biasing algorithm itself, making it extremely versatile and transparent. The method is tested on three model systems: diffusion on the Cu(001) surface and nickel-catalyzed methane decomposition, as examples of reactive processes with a bond-length-based CV, and the folding of a long polymer-like chain, using a set of dihedral angles as a CV. Boost factors up to 109, corresponding to a time scale of seconds, could be obtained while still accurately reproducing correct dynamics.

Abstract: Illicit drugs consumption and trafficking is spread worldwide and remains an increasing challenge for local authorities. Forensic drugs and their metabolites are released into wastewaters due to human excretion after illegal consumption of drugs and occasionally due to disposal of clandestine laboratory wastes into sewage systems, being recently classified as the latest group of emerging pollutants. Hence, it is essential to have efficient and accurate methods to detect these type of compounds in seized street samples, biological fluids and wastewaters in order to reduce and prevent trafficking and consumption and negative effects on aquatic systems. Electrochemical strategies offer a fast, portable, low-cost and accurate alternative to chromatographic and spectrometric methods, for the analysis of forensic drugs and metabolites in different matrices. Recent electrochemical strategies applied to the detection of illicit drugs in wastewaters, biological fluids and street samples are presented in this review, together with the impact of drug consumption on the environment.

Abstract: Water permeation between stacked layers of hBN sheets forming 2D nanochannels is investigated using large-scale ab initio-quality molecular dynamics simulations. A high-dimensional neural network potential trained on density-functional theory calculations is employed. We simulate water in van der Waals nanocapillaries and study the impact of nanometric confinement on the structure and dynamics of water using both equilibrium and nonequilibrium methods. At an interlayer distance of 10.2 A confinement induces a first-order phase transition resulting in a well-defined AA-stacked bilayer of hexagonal ice. In contrast, for h < 9 A, the 2D water monolayer consists of a mixture of different locally ordered patterns of squares, pentagons, and hexagons. We found a significant change in the transport properties of confined water, particularly for monolayer water where the water-solid friction coefficient decreases to half and the diffusion coefficient increases by a factor of 4 as compared to bulk water. Accordingly, the slip-velocity is found to increase under confinement and we found that the overall permeation is dominated by monolayer water adjacent to the hBN membranes at extreme confinements. We conclude that monolayer water in addition to bilayer ice has a major contribution to water transport through 2D nanochannels.

Abstract: Plasma-based nitrogen fixation for fertilizer production is an attractive alternative to the fossil fuel-based industrial processes. However, many factors hinder its applicability, e.g., the commonly observed inverse correlation between energy consumption and production rates or the necessity to enhance the selectivity toward NO2, the desired product for a more facile formation of nitrate-based fertilizers. In this work, we investigated the use of a rotating gliding arc plasma for nitrogen fixation at elevated pressures (up to 3 barg), at different feed gas flow rates and composition. Our results demonstrate a dramatic increase in the amount of NOx produced as a function of increasing pressure, with a record-low EC of 1.8 MJ/(mol N) while yielding a high production rate of 69 g/h and a high selectivity (94%) of NO2. We ascribe this improvement to the enhanced thermal Zeldovich mechanism and an increased rate of NO oxidation compared to the back reaction of NO with atomic oxygen, due to the elevated pressure.

Abstract: The current global energy crisis indicated that increasing our
insight into nonfossil fuel nitrogen fixation pathways for synthetic fertilizer
production is more crucial than ever. Nonequilibrium plasma is a good candidate
because it can use N2 or air as a N source and water directly as a H source, instead
of H2 or fossil fuel (CH4). In this work, we investigate NH3 gas phase formation
pathways from humid N2 and especially humid air up to 2.4 mol % H2O (100%
relative humidity at 20 °C) by optical emission spectroscopy and Fouriertransform
infrared spectroscopy. We demonstrate that the nitrogen fixation
capacity is increased when water vapor is added, as this enables HNO2 and NH3
production in both N2 and air. However, we identified a significant loss
mechanism for NH3 and HNO2 that occurs in systems where these species are
synthesized simultaneously; i.e., downstream from the plasma, HNO2 reacts with NH3 to form NH4NO2, which rapidly decomposes
into N2 and H2O. We also discuss approaches to prevent this loss mechanism, as it reduces the effective nitrogen fixation when not
properly addressed and therefore should be considered in future works aimed at optimizing plasma-based N2 fixation. In-line removal
of HNO2 or direct solvation in liquid are two proposed strategies to suppress this loss mechanism. Indeed, using liquid H2O is
beneficial for accumulation of the N2 fixation products. Finally, in humid air, we also produce NH4NO3, from the reaction of HNO3
with NH3, which is of direct interest for fertilizer application.

Abstract: Plasma catalysis is emerging for plasma-assisted gas conversion
processes. However, the underlying mechanisms of plasma catalysis are poorly
understood. In this work, we present a 1D heterogeneous catalysis model with axial
dispersion (i.e., accounting for back-mixing and molecular diffusion of fluid elements in
the process stream in the axial direction), for plasma-catalytic NO production from
N2/O2 mixtures. We investigate the concentration and reaction rates of each species
formed as a function of time and position across the catalyst, in order to determine the
underlying mechanisms. To obtain insights into how the performance of the process
can be further improved, we also study how changes in the postplasma gas flow
composition entering the catalyst bed and in the operation conditions of the catalytic
stage affect the performance of NO production.