Abstract: Cold atmospheric pressure plasmas have proven to provide an alternative treatment of cancer by targeting tumorous cells while leaving their healthy counterparts unharmed. However, the underlying mechanisms of the plasma–cell interactions are not yet fully understood. Reactive oxygen species, and in particular hydroxyl radicals (OH), are known to play a crucial role in plasma driven apoptosis of
malignant cells. In this paper we investigate the interaction of OH radicals, as well as H2O2 molecules and HO2 radicals, with DNA by means of reactive molecular dynamics simulations using the ReaxFF force field. Our results provide atomic-scale insight into the dynamics of oxidative stress on DNA caused by the OH radicals, while H2O2 molecules appear not reactive within the considered timescale. Among the observed processes are the formation of 8-OH-adduct radicals, forming the first stages towards the formation of 8-oxoGua and 8-oxoAde, H-abstraction reactions of the amines, and the partial opening of loose DNA ends in aqueous solution.

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: This paper presents the computational study of the metal-organic (MO) CVD of titanium dioxide (TiO2) films grown using titanium tetraisopropoxide (TTIP) as a precursor and nitrogen as a carrier gas. The TiO2 films are deposited under atmospheric pressure. The effects of the precursor concentration, the substrate temperature, and the hydrolysis reaction on the deposition process are investigated. It is found that hydrolysis of the TTIP decreases the onset temperature of the gas-phase thermal decomposition, and that the deposition rate increases with the precursor concentration and with the decrease of substrate temperature. Concerning the mechanism responsible for the film growth, the model shows that at the lowest precursor concentration, the direct adsorption of the precursor is dominant, while at higher precursor concentrations, the monomer deposition becomes more important.

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: We perform molecular dynamics simulations to study the flip-flop motion of phosphatidylserine (PS) across the plasma membrane upon increasing oxidation degree of the membrane. Our computational results show that an increase of the oxidation degree in the lipids leads to a decrease of the free energy barrier for translocation of PS through the membrane. In other words, oxidation of the lipids facilitates PS flip-flop motion across the membrane, because in native phospholipid bilayers this is only a “rare event” due to the high energy barriers for the translocation of PS. The present study provides an atomic-scale insight into the mechanisms of the PS flip-flop upon oxidation of lipids, as produced for example by cold atmospheric plasma, in living cells.

Abstract: Molecular dynamics simulations are used to investigate the effect of an AFM tip when indenting graphene nano bubbles filled by a noble gas (i.e. He, Ne and Ar) up to the breaking point. The failure points resemble those of viral shells as described by the Foppl-von Karman (FvK) dimensionless number defined in the context of elasticity theory of thin shells. At room temperature, He gas inside the bubbles is found to be in the liquid state while Ne and Ar atoms are in the solid state although the pressure inside the nano bubble is below the melting pressure of the bulk. The trapped gases are under higher hydrostatic pressure at low temperatures than at room temperature.

Abstract: Molecular dynamics simulations are carried out for describing growth of Pd and PdO nanoclusters using the ReaxFF force field. The resulting nanocluster structures are successfully compared to those of nanoclusters experimentally grown in a gas aggregation source. The PdO structure is quasi-crystalline as revealed by high resolution transmission microscope analysis for experimental PdO nanoclusters. The role of the nanocluster temperature in the molecular dynamics simulated growth is highlighted.

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: Reactive molecular dynamics simulations are performed to study the interaction of reactive oxygen species, such as OH, HO2 and H2O2, with the endotoxic biomolecule lipid A of the gram-negative bacterium Escherichia coli. It is found that the aforementioned plasma species can destroy the lipid A, which consequently results in reducing its toxic activity. All bond dissociation events are initiated by hydrogen-abstraction reactions. However, the mechanisms behind these dissociations are dependent on the impinging plasma species, i.e. a clear difference is observed in the mechanisms upon impact of HO2 radicals and H2O2 molecules on one hand and OH radicals on the other hand. Our simulation results are in good agreement with experimental observations.

Abstract: Plasma-catalytic CO, hydrogenation for methanol production is gaining increasing interest, but our understanding of its reaction mechanism remains primitive. We present a combined experimental/computational study on plasma-catalytic CO, hydrogenation to CH3OH over a size-selected Cu/gamma-Al2O3 catalyst. Our experiments demonstrate a synergistic effect between the Cu/gamma-Al2O3 catalyst and the CO2/H-2 plasma, achieving a CO2 conversion of 10% at 4 wt % Cu loading and a CH3OH selectivity near 50% further rising to 65% with H2O addition (for a H2O/CO2 ratio of 1). Furthermore, the energy consumption for CH3OH production was more than 20 times lower than with plasma only. We carried out density functional theory calculations over a Cu-13/gamma-Al2O3 model, which reveal that the interfacial sites of the Cu-13 cluster and gamma-Al2O3 support show a bifunctional effect: they not only activate the CO2 molecules but also strongly adsorb key intermediates to promote their hydrogenation further. Reactive plasma species can regulate the catalyst surface reactions via the Eley-Rideal (E-R) mechanism, which accelerates the hydrogenation process and promotes the generation of the key intermediates. H2O can promote the CH3OH desorption by competitive adsorption over the Cu-13/gamma-Al2O3 surface. This study provides new insights into CO2 hydrogenation through plasma catalysis, and it provides inspiration for the conversion of some other small molecules (CH4, N-2, CO, etc.) by plasma catalysis using supported-metal clusters.

Abstract: In this paper, a new implementation of the Metropolis Monte Carlo (MMC) algorithm is presented. When combining the MMC model with a molecular dynamics (MD) code, crystal growth by plasma-enhanced chemical vapor deposition can be simulated. As the MD part simulates impacts of growth species onto the surface on a time scale of picoseconds, the MMC algorithm simulates the slower adatom surface processes. The implementation includes a criterion for the selection of atoms that are allowed to be displaced during the simulation, and a criterion of after how many MMC cycles the simulation is stopped. We performed combined MD-MMC simulations for hydrocarbon species that are important for the growth of ultrananocrystalline diamond (UNCD) films at partially hydrogenated diamond surfaces, since this implementation is part of a study of the growth mechanisms of (ultra)nanocrystalline diamond films. Exemplary for adatom arrangements during the growth of UNCD, the adatom surface behavior of C and C2H2 at diamond (111)1 × 1, C and C4H2 at diamond (111)1 × 1 and C3 at diamond (100)2 × 1 has been investigated. For all cases, the diamond crystal structure is pursued under the influence of MMC simulation. Additional longer time-scale MD simulations put forward very similar structures, verifying the MMC algorithm. Nevertheless, the MMC simulation time is typically one order of magnitude shorter than the MD simulation time.

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: Industrial production of HCN from NH3 and CH4 not only uses precious Pt or Pt−Rh catalysts but also requires extremely high temperatures (∼1600 K). From an energetic, operational, and safety perspective, a drastic decrease in temperature is highly desirable. Here, we report ammonia reforming of methane for the production of HCN and H2 at 673 K by the combination of CH4/NH3 plasma and a supported Cu/silicalite-1 catalyst. 30% CH4 conversion has been achieved with 79% HCN selectivity. Catalyst characterization and plasma diagnostics reveal that the excellent reaction performance is attributed to metallic Cu active sites. In addition, we propose a possible reaction pathway, viz. E-R reactions with N, NH, NH2, and CH radicals produced in the plasma, for the production of HCN, based on density functional theory calculations. Importantly, the Cu/silicalite-1 catalyst costs less than 5% of the commercial Pt mesh catalyst.