Solubility of Hydrogen in a WMoTaNbV High-Entropy Alloy.

The WMoTaNbV alloy has shown promise for applications as a solid state hydrogen storage material. It absorbs significant quantities of H directly from the atmosphere, trapping it with high energy. In this work, the dynamics of the absorption of hydrogen isotopes are studied by determining the activation energy for the solubility and the solution enthalpy of H in the WMoTaNbV alloy. The activation energy was studied by heating samples in a H atmosphere at temperatures ranging from 20 °C to 400 °C and comparing the amounts of absorbed H. The solution activation energy EA of H was determined to be EA=0.22±0.02 eV (21.2 ± 1.9 kJ/mol). The performed density functional theory calculations revealed that the neighbouring host atoms strongly influenced the solution enthalpy, leading to a range of theoretical values from -0.40 eV to 0.29 eV (-38.6 kJ/mol to 28.0 kJ/mol).

Universal radiation tolerant semiconductor.

Radiation tolerance is determined as the ability of crystalline materials to withstand the accumulation of the radiation induced disorder. Nevertheless, for sufficiently high fluences, in all by far known semiconductors it ends up with either very high disorder levels or amorphization. Here we show that gamma/beta (γ/ß) double polymorph Ga2O3 structures exhibit remarkably high radiation tolerance. Specifically, for room temperature experiments, they tolerate a disorder equivalent to hundreds of displacements per atom, without severe degradations of crystallinity; in comparison with, e.g., Si amorphizable already with the lattice atoms displaced just once. We explain this behavior by an interesting combination of the Ga- and O- sublattice properties in γ-Ga2O3. In particular, O-sublattice exhibits a strong recrystallization trend to recover the face-centered-cubic stacking despite the stronger displacement of O atoms compared to Ga during the active periods of cascades. Notably, we also explained the origin of the ß-to-γ Ga2O3 transformation, as a function of the increased disorder in ß-Ga2O3 and studied the phenomena as a function of the chemical nature of the implanted atoms. As a result, we conclude that γ/ß double polymorph Ga2O3 structures, in terms of their radiation tolerance properties, benchmark a class of universal radiation tolerant semiconductors.

Insights into nanoparticle shape transformation by energetic ions.

Shape modification of embedded nanoparticles can be achieved by means of swift heavy ion irradiation. During irradiation, the particles elongate and align with the direction of the ion beam, presumably due to nanometer-scale phase transitions induced by individual ion impacts. However, the details of this transformation are not fully understood. The shape of metal nanoparticles embedded in dielectric matrices defines the non-linear optical properties of the composite material. Therefore, understanding the transformation process better is beneficial for producing materials with the desired optical properties. We study the elongation mechanism of gold nanoparticles using atomistic simulations. Here we focus on long-timescale processes and adhesion between the nanoparticle and the matrix. Without the necessity of ad-hoc assumptions used earlier, our simulations show that, due to adhesion with the oxide, the nanoparticles can grow in aspect ratio while in the molten state even after silicon dioxide solidifies. Moreover, they demonstrate the active role of the matrix: Only explicit simulations of ion impacts around the embedded nanoparticle provide the mechanism for continuous elongation up to experimental values of aspect ratio. Experimental transmission electron microscopy micrographs of nanoparticles after high-fluence irradiation support the simulations. The elongated nanoparticles in experiments and their interface structures with silica, as characterized by the micrographs, are consistent with the simulations. These findings bring ion beam technology forward as a precise tool for shaping embedded nanostructures for various optical applications.

Examining Different Regimes of Ionization-Induced Damage in GaN Through Atomistic Simulations.

The widespread adoption of gGaN in radiation-hard semiconductor devices relies on a comprehensive understanding of its response to strongly ionizing radiation. Despite being widely acclaimed for its high radiation resistance, the exact effects induced by ionization are still hard to predict due to the complex phase-transition diagrams and defect creation-annihilation dynamics associated with group-III nitrides. Here, the Two-Temperature Model, Molecular Dynamics simulations and Transmission Electron Microscopy, are employed to study the interaction of Swift Heavy Ions with GaN at the atomic level. The simulations reveal a high propensity of GaN to recrystallize the region melted by the impinging ion leading to high thresholds for permanent track formation. Although the effect exists in all studied electronic energy loss regimes, its efficiency is reduced with increasing electronic energy loss, in particular when there is dissociation of the material and subsequent formation of N2 bubbles. The recrystallization is also hampered near the surface where voids and pits are prominent. The exceptional agreement between the simulated and experimental results establishes the applicability of the model to examine the entire electronic energy loss spectrum. Furthermore, the model supports an empirical relation between the interaction cross sections (namely for melting and amorphization) and the electronic energy loss.

Mechanism of Spontaneous Surface Modifications on Polycrystalline Cu Due to Electric Fields.

We present a credible mechanism of spontaneous field emitter formation in high electric field applications, such as Compact Linear Collider in CERN (The European Organization for Nuclear Research). Discovery of such phenomena opens new pathway to tame the highly destructive and performance limiting vacuum breakdown phenomena. Vacuum breakdowns in particle accelerators and other devices operating at high electric fields is a common problem in the operation of these devices. It has been proposed that the onset of vacuum breakdowns is associated with appearance of surface protrusions while the device is in operation under high electric field. Moreover, the breakdown tolerance of an electrode material was correlated with the type of lattice structure of the material. Although biased diffusion under field has been shown to cause growth of significantly field-enhancing tips starting from initial nm-size protrusions, the mechanisms and the dynamics of the growth of the latter have not been studied yet. In the current paper we conduct molecular dynamics simulations of nanocrystalline copper surfaces and show the possibility of protrusion growth under the stress exerted on the surface by an applied electrostatic field. We show the importance of grain boundaries on the protrusion formation and establish a linear relationship between the necessary electrostatic stress for protrusion formation and the temperature of the system. Finally, we show that the time for protrusion formation decreases with the applied electrostatic stress, we give the Arrhenius extrapolation to the case of lower fields, and we present a general discussion of the protrusion formation mechanisms in the case of polycrystalline copper surfaces.

Machine-learning interatomic potential for W-Mo alloys.

In this work, we develop a machine-learning interatomic potential for WxMo1-xrandom alloys. The potential is trained using the Gaussian approximation potential framework and density functional theory data produced by the Viennaab initiosimulation package. The potential focuses on properties such as elastic properties, melting, and point defects for the whole range of WxMo1-xcompositions. Moreover, we use all-electron density functional theory data to fit an adjusted Ziegler-Biersack-Littmarck potential for the short-range repulsive interaction. We use the potential to investigate the effect of alloying on the threshold displacement energies and find a significant dependence on the local chemical environment and element of the primary recoiling atom.

Gradient-based training and pruning of radial basis function networks with an application in materials physics.

Many applications, especially in physics and other sciences, call for easily interpretable and robust machine learning techniques. We propose a fully gradient-based technique for training radial basis function networks with an efficient and scalable open-source implementation. We derive novel closed-form optimization criteria for pruning the models for continuous as well as binary data which arise in a challenging real-world material physics problem. The pruned models are optimized to provide compact and interpretable versions of larger models based on informed assumptions about the data distribution. Visualizations of the pruned models provide insight into the atomic configurations that determine atom-level migration processes in solid matter; these results may inform future research on designing more suitable descriptors for use with machine learning algorithms.

Core-Satellite Gold Nanoparticle Complexes Grown by Inert Gas-Phase Condensation.

Spontaneous growth of complexes consisted of a number of individual nanoparticles in a controlled manner, particularly in demanding environments of gas-phase synthesis, is a fascinating opportunity for numerous potential applications. Here, we report the formation of such core-satellite gold nanoparticle structures grown by magnetron sputtering inert gas condensation. Combining high-resolution scanning transmission electron microscopy and computational simulations, we reveal the adhesive and screening role of H2O molecules in formation of stable complexes consisted of one nanoparticle surrounded by smaller satellites. A single layer of H2O molecules, condensed between large and small gold nanoparticles, stabilizes positioning of nanoparticles with respect to one another during milliseconds of the synthesis time. The lack of isolated small gold nanoparticles on the substrate is explained by Brownian motion that is significantly broader for small-size particles. It is inferred that H2O as an admixture in the inert gas condensation opens up possibilities of controlling the final configuration of the different noble metal nanoparticles.

Data sets and trained neural networks for Cu migration barriers.

Kinetic Monte Carlo (KMC) is an efficient method for studying diffusion. A limiting factor to the accuracy of KMC is the number of different migration events allowed in the simulation. Each event requires its own migration energy barrier. The calculation of these barriers may be unfeasibly expensive. In this article we present a data set of migration barriers on for nearest-neighbour jumps on the Cu surfaces, calculated with the nudged elastic band (NEB) method and the tethering force approach. We used the data to train artificial neural networks (ANN) in order to predict the migration barriers for arbitrary nearest-neighbour Cu jumps. The trained ANNs are also included in the article. The data is hosted by the CSC IDA storage service.

Dynamic coupling between particle-in-cell and atomistic simulations.

We propose a method to directly couple molecular dynamics, the finite element method, and particle-in-cell techniques to simulate metal surface response to high electric fields. We use this method to simulate the evolution of a field-emitting tip under thermal runaway by fully including the three-dimensional space-charge effects. We also present a comparison of the runaway process between two tip geometries of different widths. The results show with high statistical significance that in the case of sufficiently narrow field emitters, the thermal runaway occurs in cycles where intensive neutral evaporation alternates with cooling periods. The comparison with previous works shows that the evaporation rate in the regime of intensive evaporation is sufficient to ignite a plasma arc above the simulated field emitters.

Growth mechanism for nanotips in high electric fields.

In this work we show using atomistic simulations that the biased diffusion in high electric field gradients creates a mechanism whereby nanotips may start growing from small surface asperities. It has long been known that atoms on a metallic surface have biased diffusion if electric fields are applied and that microscopic tips may be sharpened using fields, but the exact mechanisms have not been well understood. Our Kinetic Monte Carlo simulation model uses a recently developed theory for how the migration barriers are affected by the presence of an electric field. All parameters of the model are physically motivated and no fitting parameters are used. The model has been validated by reproducing characteristic faceting patterns of tungsten surfaces that have in previous experiments been observed to only appear in the presence of strong electric fields. The growth effect is found to be enhanced by increasing fields and temperatures.

Structural properties of protective diamond-like-carbon thin films grown on multilayer graphene.

In spite of the versatility of electronic properties of graphene, its fragility and low resistance to damage and external deformations reduce the practical value of this material for many applications. Coating of graphene with a thin layer of hard amorphous carbon is considered as a viable solution to protect the 2D material against accidental scratches and other external damaging impacts. In this study, we investigate the relationship between the deposition condition and quality of diamond-like-carbon (DLC) on top of multilayer graphene by means of molecular dynamics simulations. Deposition of carbon atoms with 70 eV incident energy at 100 K resulted in the highest content of [Formula: see text]-bonded C atoms. An increase of the number of dangling bonds at the interface between the top graphene layer and the DLC film indicates that decrease of the incident energy reduces the adhesion quality of DLC thin film on graphene. Analysis of radial distribution function indicates that [Formula: see text] hybridized carbon atoms tend to grow near already existing [Formula: see text]-atoms. This explains why the quality of the DLC structures grown on graphene have generally a lower content of [Formula: see text] C atoms compared to those grown directly on diamond. Ring analysis further shows that a DLC structure grown on the [Formula: see text]-rich structures like graphene contains a higher fraction of disordered ring structures.

Site-Specific Wetting of Iron Nanocubes by Gold Atoms in Gas-Phase Synthesis.

A key challenge in nanotechnology is the rational design of multicomponent materials that beat the properties of their elemental counterparts. At the same time, when considering the material composition of such hybrid nanostructures and the fabrication process to obtain them, one should favor the use of nontoxic, abundant elements in view of the limited availability of critical metals and sustainability. Cluster beam deposition offers a solvent- and, therefore, effluent-free physical synthesis method to achieve nanomaterials with tailored characteristics. However, the simultaneous control of size, shape, and elemental distribution within a single nanoparticle in a small-size regime (sub-10 nm) is still a major challenge, equally limiting physical and chemical approaches. Here, a single-step nanoparticle fabrication method based on magnetron-sputtering inert-gas condensation is reported, which relies on selective wetting of specific surface sites on precondensed iron nanocubes by gold atoms. Using a newly developed Fe-Au interatomic potential, the growth mechanism is decomposed into a multistage model implemented in a molecular dynamics simulation framework. The importance of growth kinetics is emphasized through differences between structures obtained either experimentally or computationally, and thermodynamically favorable configurations determined via global optimization techniques. These results provide a roadmap for engineering complex nanoalloys toward targeted applications.

Direct observation of vacuum arc evolution with nanosecond resolution.

Sufficiently high voltage applied between two metal electrodes, even in ultra high vacuum conditions, results in an inevitable discharge that lights up the entire gap, opening a conductive channel through the vacuum and parasitically consuming large amounts of energy. Despite many efforts to understand the processes that lead to this phenomenon, known as vacuum arc, there is still no consensus regarding the role of each electrode in the evolution of such a momentous process as lightning. Employing a high-speed camera, we capture the entire lightning process step-by-step with a nanosecond resolution and find which of the two electrodes holds the main responsibility for igniting the arc. The light that gradually expands from the positively charged electrode (anode), often is assumed to play the main role in the formation of a vacuum arc. However, both the nanosecond-resolution images of vacuum arc evolution and the corresponding theoretical calculations agree that the conductive channel between the electrodes is built in the form of cathodic plasma long before any significant activity develops in the anode. We show evidently that the anode illumination is weaker and plays a minor role in igniting and maintaining the conductive channel.

Highly active single-layer MoS2 catalysts synthesized by swift heavy ion irradiation.

Two-dimensional molybdenum-disulfide (MoS2) catalysts can achieve high catalytic activity for the hydrogen evolution reaction upon appropriate modification of their surface. The intrinsic inertness of the compound's basal planes can be overcome by either increasing the number of catalytically active edge sites or by enhancing the activity of the basal planes via a controlled creation of sulfur vacancies. Here, we report a novel method of activating the MoS2 surface using swift heavy ion irradiation. The creation of nanometer-scale structures by an ion beam, in combination with the partial sulfur depletion of the basal planes, leads to a large increase of the number of low-coordinated Mo atoms, which can form bonds with adsorbing species. This results in a decreased onset potential for hydrogen evolution, as well as in a significant enhancement of the electrochemical current density by over 160% as compared to an identical but non-irradiated MoS2 surface.

Data sets of migration barriers for atomistic Kinetic Monte Carlo simulations of Cu self-diffusion via first nearest neighbour atomic jumps.

Atomistic rigid lattice Kinetic Monte Carlo (KMC) is an efficient method for simulating nano-objects and surfaces at timescales much longer than those accessible by molecular dynamics. A laborious and non-trivial part of constructing any KMC model is, however, to calculate all migration barriers that are needed to give the probabilities for any atom jump event to occur in the simulations. We have calculated three data sets of migration barriers for Cu self-diffusion with two different methods. The data sets were specifically calculated for rigid lattice KMC simulations of copper self-diffusion on arbitrarily rough surfaces, but can be used for KMC simulations of bulk diffusion as well.

Data sets of migration barriers for atomistic Kinetic Monte Carlo simulations of Fe self-diffusion.

Atomistic rigid lattice Kinetic Monte Carlo (KMC) is an efficient method for simulating nano-objects and surfaces at timescales much longer than those accessible by molecular dynamics. A laborious and non-trivial part of constructing any KMC model is, however, to calculate all migration barriers that are needed to give the probabilities for any atom jump event to occur in the simulations. We calculated three data sets of migration barriers for Fe self-diffusion: barriers of first nearest neighbour jumps, second nearest neighbours hop-on jumps on the Fe {100} surface and a set of barriers of the diagonal exchange processes for various cases of the local atomic environments within the 2nn coordination shell.

Directional Sensitivity in Light-Mass Dark Matter Searches with Single-Electron-Resolution Ionization Detectors.

We propose a method using solid state detectors with directional sensitivity to dark matter interactions to detect low-mass weakly interacting massive particles (WIMPs) originating from galactic sources. In spite of a large body of literature for high-mass WIMP detectors with directional sensitivity, no available technique exists to cover WIMPs in the mass range <1 GeV/c^{2}. We argue that single-electron-resolution semiconductor detectors allow for directional sensitivity once properly calibrated. We examine the commonly used semiconductor material response to these low-mass WIMP interactions.

Au nanowire junction breakup through surface atom diffusion.

Metallic nanowires are known to break into shorter fragments due to the Rayleigh instability mechanism. This process is strongly accelerated at elevated temperatures and can completely hinder the functioning of nanowire-based devices like e.g. transparent conductive and flexible coatings. At the same time, arranged gold nanodots have important applications in electrochemical sensors. In this paper we perform a series of annealing experiments of gold and silver nanowires and nanowire junctions at fixed temperatures 473, 673, 873 and 973 K (200 °C, 400 °C, 600 °C and 700 °C) during a time period of 10 min. We show that nanowires are especially prone to fragmentation around junctions and crossing points even at comparatively low temperatures. The fragmentation process is highly temperature dependent and the junction region breaks up at a lower temperature than a single nanowire. We develop a gold parametrization for kinetic Monte Carlo simulations and demonstrate the surface diffusion origin of the nanowire junction fragmentation. We show that nanowire fragmentation starts at the junctions with high reliability and propose that aligning nanowires in a regular grid could be used as a technique for fabricating arrays of nanodots.

Formation Mechanism of Fe Nanocubes by Magnetron Sputtering Inert Gas Condensation.

In this work, we study the formation mechanisms of iron nanoparticles (Fe NPs) grown by magnetron sputtering inert gas condensation and emphasize the decisive kinetics effects that give rise specifically to cubic morphologies. Our experimental results, as well as computer simulations carried out by two different methods, indicate that the cubic shape of Fe NPs is explained by basic differences in the kinetic growth modes of {100} and {110} surfaces rather than surface formation energetics. Both our experimental and theoretical investigations show that the final shape is defined by the combination of the condensation temperature and the rate of atomic deposition onto the growing nanocluster. We, thus, construct a comprehensive deposition rate-temperature diagram of Fe NP shapes and develop an analytical model that predicts the temporal evolution of these properties. Combining the shape diagram and the analytical model, morphological control of Fe NPs during formation is feasible; as such, our method proposes a roadmap for experimentalists to engineer NPs of desired shapes for targeted applications.