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: The recent energy crisis revealed that there is a strong need to replace hydrocarbon-fueled industrial nitrogen fixation processes by alternative, more sustainable methods. In light of this, plasma-based nitrogen fixation remains one of the most promising options, considering both theoretical and experimental aspects. Lately, plasma interacting with water has received considerable attention in nitrogen fixation applications as it can trigger a unique gas- and liquid-phase chemistry. Within this context, a critical exploration of plasma-assisted nitrogen fixation with or without water presence is of great interest with an emphasis on energy costs, particularly in plasma reactors which have potential for large-scale industrial application. In this work, the presence of water in a multi-pin plasma system on nitrogen oxidation is experimentally investigated by comparing two pulsed negative DC voltage plasmas in metal–metal and metal–liquid electrode configurations. The plasma setups are designed to create similar plasma properties, including plasma power and discharge regime in both configurations. The system energy cost is calculated, considering nitrogen-containing species generated in gas and liquid phases as measured by a gas analyzer, nitrate sensor, and a colorimetry method. The energy cost profile as a function of specific energy input showed a strong dependency on the plasma operational frequency and the gas flow rate, as a result of different plasma operation regimes and initiated reverse processes. More importantly, the presence of the plasma/liquid interface increased the energy cost up to 14 ± 8%. Overall, the results showed that the presence of water in the reaction zone has a negative impact on the nitrogen fixation process.

Abstract: Plasma medicine, or the biomedical application of cold atmospheric plasma (CAP), is an expanding field within plasma research. CAP has demonstrated remarkable versatility in diverse biological applications, including cancer treatment, wound healing, microorganism inactivation, and skin disease therapy. However, the precise mechanisms underlying the effects of CAP remain incompletely understood. The therapeutic effects of CAP are largely attributed to the generation of reactive oxygen and nitrogen species (RONS), which play a crucial role in the biological responses induced by CAP. Specifically, RONS produced during CAP treatment have the ability to chemically modify cell membranes and membrane proteins, causing nitro-oxidative stress, thereby leading to changes in membrane permeability and disruption of cellular processes. To gain atomic-level insights into these interactions, non-reactive molecular dynamics (MD) simulations have emerged as a valuable tool. These simulations facilitate the examination of larger-scale system dynamics, including protein-protein and protein-membrane interactions. In this comprehensive review, we focus on the applications of non-reactive MD simulations in studying the effects of CAP on cellular components and interactions at the atomic level, providing a detailed overview of the potential of CAP in medicine. We also review the results of other MD studies that are not related to plasma medicine but explore the effects of nitro-oxidative stress on cellular components and are therefore important for a broader understanding of the underlying processes.

Abstract: In recent years there has been growing interest in the use of low-temperature atmospheric pressure plasmas for biomedical applications. Currently, however, there is very little fundamental knowledge regarding the relevant interaction mechanisms of plasma species with living cells. In this paper, we investigate the interaction of important plasma species, such as O3, O2 and O atoms, with bacterial peptidoglycan (or murein) by means of reactive molecular dynamics simulations. Specifically, we use the peptidoglycan structure to model the gram-positive bacterium Staphylococcus aureus murein. Peptidoglycan is the outer protective barrier in bacteria and can therefore interact directly with plasma species. Our results demonstrate that among the species mentioned above, O3 molecules and especially O atoms can break important bonds of the peptidoglycan structure (i.e. CO, CN and CC bonds), which subsequently leads to the destruction of the bacterial cell wall. This study is important for gaining a fundamental insight into the chemical damaging mechanisms of the bacterial peptidoglycan structure on the atomic scale.

Abstract: The reaction behavior of species that may affect the growth of ultrananocrystal line and nanocrystalline diamond ((U)NCD) films is investigated by means of molecular dynamics simulations. Impacts of CHx (x = 0 – 4), C2Hx (x=0-6), C3Hx (x=0-2), C4Hx (x = 0 – 2), H, and H-2 on clean and hydrogenated diamond (100)2 x 1 and (111) 1 x 1 surfaces at two different substrate temperatures are simulated. We find that the different bonding structures of the two surfaces cause different temperature effects on the sticking efficiency. These results predict a temperature-dependent ratio of diamond (100) and (111) growth. Furthermore, predictions of which are the most important hydrocarbon species for (U)NCD growth are made.

Abstract: A multi-species Monte Carlo (MC) model, combined with an analytical surface model, has been developed in order to investigate the general plasma processes occurring during the sputter deposition of complex oxide films in a dual-magnetron sputter deposition system. The important plasma species, such as electrons, Ar+ ions, fast Ar atoms and sputtered metal atoms (i.e. Mg and Al atoms) are described with the so-called multi-species MC model, whereas the deposition of MgxAlyOz films is treated by an analytical surface model. Targetsubstrate distances for both magnetrons in the dual-magnetron setup are varied for the purpose of growing stoichiometric complex oxide thin films. The metal atoms are sputtered from pure metallic targets, whereas the oxygen flux is only directed toward the substrate and is high enough to obtain fully oxidized thin films but low enough to avoid target poisoning. The calculations correspond to typical experimental conditions applied to grow these complex oxide films. In this paper, some calculation results are shown, such as the densities of various plasma species, their fluxes toward the targets and substrate, the deposition rates, as well as the film stoichiometry. Moreover, some results of the combined model are compared with experimental observations. Note that this is the first complete model, which can be applied for large and complicated magnetron reactor geometries, such as dual-magnetron configurations. With this model, we are able to describe all important plasma species as well as the deposition process. It can also be used to predict film stoichiometries of complex oxide films on the substrate.

Abstract: Dielectric Barrier Discharges operating in CO and CO2 form solid products at atmospheric pressure. The main differences between both plasmas and their deposits were analyzed, at similar energy input. GC measurements revealed a mixture of CO2, CO, and O2 in the CO2 DBD exhaust, while no O2 was found in the CO plasma. A coating of nanoparticles composed of Fe, O, and C was produced by the CO2 discharge, whereas, a microscopic dendrite-like carbon structure was formed in the CO plasma. Fe3O4 and Fe crystalline phases were found in the CO2 sample. The CO
deposition was characterized as an amorphous structure, close to polymeric CO (p-CO). Interestingly, p-CO is not formed in the CO2 plasma, in spite of the significant amounts of CO produced (up to 30% in the reactor exhaust).

Abstract: An extensive CO2 plasmamodel is presented that is relevant for the production of ‘‘solar fuels.’’ It is based on reaction rate coefficients fromrigorously reviewed literature, and is augmented with reactionrate coefficients that are obtained fromscaling laws.The input data set,which is suitable for usage with the plasma simulation software Plasimo (https://plasimo.phys.tue.nl/), is available via the Plasimo and publisher’s websites.1 The correctness of this model implementation has been established by independent ZDPlasKin implementation (http://www.zdplaskin.
laplace.univ-tlse.fr/), to verify that the results agree. Results of these ‘‘global models’’ are presented for a DBD plasma reactor.

Abstract: The modelling of a gliding arc discharge (GAD) is studied by means of the quasineutral (QN) plasma modelling approach. The model is first evaluated for reliability and proper description of a gliding arc discharge at atmospheric pressure, by comparing with a more elaborate non-quasineutral (NQN) plasma model in two different geometries – a 2D axisymmetric and a Cartesian geometry. The NQN model is considered as a reference, since it provides a continuous self-consistent plasma description, including the near electrode regions. In general, the results of the QN model agree very well with those obtained from the NQN model. The small differences between both models are attributed to the approximations in the derivation of the QN model. The use of the QN model provides a substantial reduction of the computation time compared to the NQN model, which is crucial for the development of more complex models in three dimensions or with complicated chemistries. The latter is illustrated for (i) a reverse vortex flow(RVF) GAD in argon, and (ii) a GAD in CO2. The RVF discharge is modelled in three dimensions and the effect of the turbulent heat transport on the plasma and gas characteristics is
discussed. The GAD model in CO2 is in a 1D geometry with axial symmetry and provides results for the time evolution of the electron, gas and vibrational temperature of CO2, as well as for the molar fractions of the different species.

Abstract: This paper gives an overview of our plasma chemistry modeling for CO2 and CH4 conversion in a dielectric barrier discharge (DBD) and microwave (MW) plasma. We focus on pure CO2 splitting and pure CH4 reforming, as well as mixtures of CO2/CH4, CH4/O2, and CO2/H2O. We show calculation results for the conversion, energy efficiency, and product formation, in comparison with experiments where possible. We also present the underlying chemical reaction pathways, to explain the observed
trends. For pure CO2, a comparison is made between a DBD and MW plasma, illustrating that the higher energy efficiency of the latter is attributed to the more important role of the vibrational levels.

Abstract: The catalytic oxidative dehydrogenation of hydrocarbons is an industrially important process, in which selectivity is a key issue. We here investigate the conversion of methanol to formaldehyde on a vanadia surface employing long timescale simulations, reaching a time scale of seconds. In particular, we compare the thermal process to the case where an additional external electric field is applied, as would be the case in a direct plasma-catalysis setup. We find that the electric field influences the retention time of the molecules at the catalyst surface. These simulations provide an atomic scale insight in the thermal catalytic oxidative dehydrogenation process, and in how an external electric field may affect this process.

Abstract: Cryogenic plasma etching is a promising technique for high-control wafer development with limited plasma induced damage. Cryogenic wafer temperatures effectively reduce surface damage during etching, but the fundamental mechanism is not well understood. In this study, the influences of wafer temperature, gas mixture and substrate bias on the (cryogenic) etch rates of Si with SF6/O2 inductively coupled plasmas are experimentally and computationally investigated. The etch rates are measured in situ with double-point reflectometry and a hybrid computational Monte Carlo – fluid model is applied to calculate plasma properties. This work allows the reader to obtain a better insight in the effects of wafer temperature on the etch rate and to find operating conditions for successful anisotropic (cryo)etching.