Abstract: Catalyst preparation with plasmas is increasingly attracting interest. A plasma is a partially ionized gas, consisting of electrons, ions, molecules, radicals, photons, and excited species, which are all active species for catalyst preparation and treatment. Under the influence of plasma, nucleation and crystal growth in catalyst preparation can be very different from those in the conventional thermal approach. Some thermodynamically unfavorable reactions can easily take place with plasmas. Compounds such as sulfides, nitrides, and phosphides that are produced under harsh conditions can be synthesized by plasma under mild conditions. Plasmas can produce catalysts with smaller particle sizes and controllable structure. Plasma is also a facile tool for reduction, oxidation, doping, etching, coating, alloy formation, surface treatment, and surface cleaning in a simple and direct way. A rapid and convenient plasma template removal has thus been established for zeolite synthesis. It can operate at room temperature and allows the catalyst preparation on temperature-sensitive supporting materials. Plasma is typically effective for the production of various catalysts on metallic substrates. In addition, plasma-prepared transition-metal catalysts show enhanced low-temperature activity with improved stability. This provides a useful model catalyst for further improvement of industrial catalysts. In this review, we aim to summarize the recent advances in catalyst preparation with plasmas. The present understanding of plasma-based catalyst preparation is discussed. The challenges and future development are addressed.

Abstract: New & beta;-stabilizedTi-based alloys are highly promising forbone implants, thanks in part to their low elasticity. The natureof this elasticity, however, is as yet unknown. We here present combinedfirst-principles DFT calculations and experiments on the microstructure,structural stability, mechanical characteristics, and electronic structureto elucidate this origin. Our results suggest that the studied & beta;Ti-35Nb-7Zr-5Ta wt % (TNZT) alloy manufacturedby the electron-beam powder bed fusion (E-PBF) method has homogeneousmechanical properties (H = 2.01 & PLUSMN; 0.22 GPa and E = 69.48 & PLUSMN; 0.03 GPa) along the building direction,which is dictated by the crystallographic texture and microstructuremorphologies. The analysis of the structural and electronic properties,as the main factors dominating the chemical bonding mechanism, indicatesthat TNZT has a mixture of strong metallic and weak covalent bonding.Our calculations demonstrate that the softening in the Cauchy pressure(C & PRIME; = 98.00 GPa) and elastic constant C ̅ ( 44 ) = 23.84 GPa is the originof the low elasticity of TNZT. Moreover, the nature of this softeningphenomenon can be related to the weakness of the second and thirdneighbor bonds in comparison with the first neighbor bonds in theTNZT. Thus, the obtained results indicate that a carefully designedTNZT alloy can be an excellent candidate for the manufacturing oforthopedic internal fixation devices. In addition, the current findingscan be used as guidance not only for predicting the mechanical propertiesbut also the nature of elastic characteristics of the newly developedalloys with yet unknown properties.

Abstract: While it is well-known that the plasma-enhanced catalytic chemical vapor deposition (PECVD) of carbon nanotubes (CNTs) offers a number of advantages over thermal CVD, the influence of the various individual contributing factors is not well understood. Especially the role of ions is unclear, since ions in plasmas are generally associated with sputtering rather than with growing a material. Even so, various studies have demonstrated the beneficial effects of ion bombardment during the growth of CNTs. This review looks at the role of the ions in plasma-enhanced CNT growth as deduced from both experimental and simulation studies. Specific attention is paid to the beneficial effects of ion bombardment. Based on the available literature, it can be concluded that ions can be either beneficial or detrimental for carbon nanotube growth, depending on the exact conditions and the control over the growth process.

Abstract: Plasma catalysis is an emerging new technology for the electrification and downscaling of NH3 synthesis. Increasing attention is being paid to the optimization of plasma catalysis with respect to the plasma conditions, the catalyst material, and their mutual interaction. In this work we use microkinetic models to study how the total conversion process is impacted by the combination of different plasma conditions and transition metal catalysts. We study how plasma-generated radicals and vibrationally excited N2 (present in a dielectric barrier discharge plasma) interact with the catalyst and impact the NH3 turnover frequencies (TOFs). Both filamentary and uniform plasmas are studied, based on plasma chemistry models that provided plasma phase speciation and vibrational distribution functions. The Langmuir−Hinshelwood reaction rate coefficients (i.e., adsorption reactions and subsequent reactions among adsorbates) are determined using conventional scaling relations. An additional set of Eley−Rideal reactions (i.e., direct reactions of plasma radicals with adsorbates) was added and a sensitivity analysis on the assumed reaction rate coefficients was performed. We first show the impact of different vibrational distribution functions on the catalytic dissociation of N2 and subsequent production of NH3, and we gradually include more radical reactions, to illustrate the contribution of these species and their corresponding reaction pathways. Analysis over a large range of catalysts indicates that different transition metals (metals such as Rh, Ni, Pt, and Pd) optimize the NH3TOFs depending on the population of the vibrational levels of N2. At higher concentrations of plasma-generated radicals, the NH3 TOFs become less dependent on the catalyst material, due to radical adsorptions on the more noble catalysts and Eley−Rideal reactions on the less noble catalysts.

Abstract: The application of nonthermal atmospheric pressure plasma is emerging as an alternative and efficient technique for the inactivation of bacterial biofilms. In this study, reactive molecular dynamics simulations were used to examine the reaction mechanisms of hydroxyl radicals, as key reactive oxygen plasma species in biological systems, with several organic molecules (i.e., alkane, alcohol, carboxylic acid, and amine), as prototypical components of biomolecules in the biofilm. Our results demonstrate that organic molecules containing hydroxyl and carboxyl groups may act as trapping agents for the OH radicals. Moreover, the impact of OH radicals on N-acetyl-glucosamine, as constituent component of staphylococcus epidermidis biofilms, was investigated. The results show how impacts of OH radicals lead to hydrogen abstraction and subsequent molecular damage. This study thus provides new data on the reaction mechanisms of plasma species, and particularly the OH radicals, with fundamental components of bacterial biofilms.

Abstract: Hydroxyapatite (HAP) is frequently used as biocompatible coating on Ti-based implants. In this context, the HAP-Ti adhesion is of crucial importance. Here, we report ab initio calculations to investigate the influence of Si incorporation into the amorphous calcium-phosphate (a-HAP) structure on the interfacial bonding mechanism between the a-HAP coating and an amorphous titanium dioxide (a-TiO2) substrate, contrasting two different density functionals: PBE-GGA, and DFT-D3, which are capable of describing the influence of the van der Waals (vdW) interactions. In particular, we discuss the effect of dispersion on the work of adhesion (W-ad), equilibrium geometries, and charge density difference (CDD). We find that replacement of P by Si in a-HAP (a-Si-HAP) with the creation of OH vacancies as charge compensation results in a significant increase in the bond strength between the coating and substrate in the case of using the PBE-GGA functional. However, including the vdW interactions shows that these forces considerably contribute to the W-ad. We show that the difference (W-ad – W-ad(vdW)) is on average more than 1.1 J m(-2) and 0.5 J m(-2) for a-HAP/a-TiO2 and a-Si-HAP/a-TiO2, respectively. These results reveal that including vdW interactions is essential for accurately describing the chemical bonding at the a-HAP/a-TiO2 interface.

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.

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: 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.