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: 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: The safe and efficient use of hydrogen energy, which is in high demand worldwide today, requires efficient hydrogen storage. Despite significant advances in hydrogen storage using carbon-based nanomaterials, including carbon nanotubes (CNTs), efforts to substantially increase the storage capacity remain less effective. In this work, we demonstrate the effect of endohedral transition metal atoms on the hydrogen storage capacity of CNTs using reactive molecular dynamics simulations. We find that an increase in the volume fraction of endohedral nickel atoms leads to an increase in the concentration of physisorbed hydrogen molecules around single-walled CNTs (SWNTs) by approximately 1.6 times compared to pure SWNTs. The obtained results provide insight into the underlying mechanisms of how endohedral transition metal atoms enhance the hydrogen storage ability of SWNTs under nearly ambient conditions.

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: The possibility of application of nanomaterials is determined by our ability to control the properties of the materials, which are ultimately determined by their structure and hence their growth processes. We employ hybrid molecular dynamics / Monte Carlo (MD/MC) simulations to explore the growth of SWNTs and graphene on nickel as a catalyst, with the specific goal of unraveling the growth mechanisms. While the general observations are in agreement with the literature, we find a number of interesting phenomena to be operative which are crucial for the growth, and which are not accessible by MD simulations alone due to the associated time scale. Specifically, we observe metal mediated healing and restructuring processes to take place, reorganizing the carbon network during the initial nucleation step. In the case of carbon nanotube growth, this leads to the growth of tubes with a determinable chirality. In the case of graphene formation, we find that graphene is only formed at temperatures above 700 K. These results are of importance for understanding the growth mechanisms of these carbon nanomaterials on the fundamental level.

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: In this paper, we present the results of combined molecular dynamics−Metropolis Monte Carlo (MD-MMC) simulations of hydrocarbon species at flat diamond (100)2 × 1 and (111)1 × 1 surfaces. The investigated species are considered to be the most important growth species for (ultra)nanocrystalline diamond ((U)NCD) growth. When applying the MMC algorithm to stuck species at monoradical sites, bonding changes are only seen for CH2. The sequence of the bond breaking and formation as put forward by the MMC simulations mimics the insertion of CH2 into a surface dimer as proposed in the standard growth model of diamond. For hydrocarbon species attached to two adjacent radical (biradical) sites, the MMC simulations give rise to significant changes in the bonding structure. For UNCD, the combinations of C3 and C3H2, and C3 and C4H2 (at diamond (100)2 × 1) and C and C2H2 (at diamond (111)1 × 1) are the most successful in nucleating new crystal layers. For NCD, the following combinations pursue the diamond structure the best: C2H2 and C3H2 (at diamond (100)2 × 1) and CH2 and C2H2 (at diamond (111)1 × 1). The different behaviors of the hydrocarbon species at the two diamond surfaces are related to the different sterical hindrances at the diamond surfaces.

Abstract: In this paper we employ first-principles calculations to investigate the effect of substitutional Si doping in the amorphous calcium-phosphate (a-HAP) structure on the work of adhesion, integral charge transfer, charge density difference and theoretical tensile strengths between an a-HAP coating and amorphous titanium dioxide (a-TiO2) substrate systemically. Our calculations demonstrate that substitution of a P atom by a Si atom in a-HAP (a-Si-HAP) with the creation of OH-vacancies as charge compensation results in a significant increase of the bonding strength of the coating to the substrate. The work of adhesion of the optimized Si-doped interfaces reaches a value of up to -2.52 J m(-2), which is significantly higher than for the stoichiometric a-HAP/a-TiO2. Charge density difference analysis indicates that the dominant interactions at the interface have significant covalent character, and in particular two Ti-O and three Ca-O bonds are formed for a-Si-HAP/a-TiO2 and one Ti-O and three Ca-O bonds for a-HAP/a-TiO2. From the stress-strain curve, the Young's modulus of a-Si-HAP/a-TiO2 is calculated to be about 25% higher than that of the a-HAP/a-TiO2, and the yielding stress is about 2 times greater than that of the undoped model. Our calculations therefore demonstrate that the presence of Si in the a-HAP structure strongly alters not only the bioactivity and resorption rates, but also the mechanical properties of the a-HAP/a-TiO2 interface. The results presented here provide an important theoretical insight into the nature of the chemical bonding at the a-HAP/a-TiO2 interface, and are particularly significant for the practical medical applications of HAP-based biomaterials.

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: In this paper, the effects of prolonged bias-enhanced nucleation (prolonged BEN) on the growth mechanisms of diamond are investigated by molecular dynamics (MD) and combined MD-Metropolis Monte Carlo (MD-MMC) simulations. First, cumulative impacts of CxHy+ and Hx+ on an a-C:H/nanodiamond composite were simulated; second, nonconsecutive impacts of the dominant ions were simulated in order to understand the observed phenomena in more detail. As stated in the existing literature, the growth of diamond structures during prolonged BEN is a process that takes place below the surface of the growing film. The investigation of the penetration behavior of CxHy+ and Hx+ species shows that the carbon-containing ions remain trapped within this amorphous phase where they dominate mechanisms like precipitation of sp3 carbon clusters. The H+ ions, however, penetrate into the crystalline phase at high bias voltages (>100 V), destroying the perfect diamond structure. The experimentally measured reduction of grain sizes at high bias voltage, reported in the literature, might thus be related to penetrating H+ ions. Furthermore, the CxHy+ ions are found to be the most efficient sputtering agents, preventing the build up of defective material.

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.