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Due to virtually no solubility, He atoms implanted or created inside materials tend to form bubbles, which are known to damage material properties through embrittlement. Higher He density in nano-sized bubbles was observed both experimentally and computationally in Ni ( 100 − x ) Fex-alloy samples compared to Ni. The bubbles in the Ni ( 100 − x ) Fex-alloys were observed to be faceted, whereas in elemental Ni they were more spherical. Molecular dynamics simulations showed that stacking fault structures formed around bubbles at maximum He density. Higher Fe concentrations stabilize stacking fault structures, suppress evolution of dislocation network around bubbles and suppress complete dislocation emission, leading to higher He density.

As a promising material for quantum technology, silicon carbide (SiC) has attracted great interest in materials science. Carbon vacancy is a dominant defect in 4H-SiC. Thus, understanding the properties of this defect is critical to its application, and the atomic and electronic structures of the defects needs to be identified. In this study, density functional theory was used to characterize the carbon vacancy defects in hexagonal (h) and cubic (k) lattice sites. The zero-phonon line energies, hyperfine tensors, and formation energies of carbon vacancies with different charge states (2−, −, 0,+ and 2+) in different supercells (72, 128, 400 and 576 atoms) were calculated using standard Perdew-Burke-Ernzerhof and Heyd-Scuseria-Ernzerhof methods. Results show that the zero-phonon line energies of carbon vacancy defects are much lower than those of divacancy defects, indicating that the former is more likely to reach the excited state than the latter. The hyperfine tensors of VC+(h) and VC+(k) were calculated. Comparison of the calculated hyperfine tensor with the experimental results indicates the existence of carbon vacancies in SiC lattice. The calculation of formation energy shows that the most stable carbon vacancy defects in the material are VC2+(k), VC+(k), VC(k), VC−(k) and VC2−(k) as the electronic chemical potential increases.

Defect evolution under irradiation is investigated in a set of single-phase concentrated solid solution alloys (SP-CSAs) containing Ni with Co, Fe and/or Cr. We show that atomic segregation of Ni takes place already at very early stages of radiation damage in the 2-4 element SP-CSAs containing Fe or Cr, well below 1 dpa. We arrive at this conclusion by following the evolution of positron annihilation signals as a function of irradiation dose in single crystal samples, complemented by molecular dynamics simulations in the same model systems for high entropy alloys (HEAs). This manifestation of short-range order calls attention to composition fluctuations at the atomic level in irradiated HEAs. Ion irradiation may induce short-range order in certain alloys due to chemically biased elemental diffusion. The work highlights the necessity of updating the assumption of a totally random arrangement in the irradiated alloys, even though the alloys before irradiation have random arrangements of different chemical elements. (C) 2020 Acta Materialia Inc. Published by Elsevier Ltd.

The mechanism of the shape elongation of metal nanoparticles (NPs) in silica, which is induced under swift heavy ion irradiation, is discussed with comparing the two candidates: (i) the synergy between the ion hammering and the transient melting of NPs by the inelastic thermal spike and (ii) the thermal pressure and flow model. We show that three experimental results are inconsistent with (i). The latter is supported by two-temperature molecular dynamics simulations, which simulate not only the atomic motions but also the local electron temperatures. A remarkable correlation was observed between the temporal evolution of the silica density around the ion trajectory and that of the aspect ratio of the NP later than similar to 1 ps after the ion impact, while no correlation was observed earlier than similar to 1 ps, even under the assumption of the instantaneous energy deposition.

Patterns on sand generated by blowing winds are one of the most commonly seen phenomena driven by such a self-organization process, as has been observed at the nanoscale after ion irradiation. The origins of this effect have been under debate for decades. Now, a new methodology allows to simulate directly the ripple formation by high-fluence ion-irradiation. Since this approach does not pre-assume a mechanism to trigger self-organization, it can provide answers to the origin of the ripple formation mechanism. The surface atom displacement and a pile-up effect are the driving force of ripple formation, analogously to the macroscopic one. IMPACT STATEMENT The presented model allows to follow the ripple formation and propagation in different steps, at the atomic level, for the first time under low irradiation energies.

Characterization of the primary damage is the starting point in describing and predicting the irradiation-induced damage in materials. So far, primary damage has been described by traditional interatomic potentials in molecular dynamics simulations. Here, we employ a Gaussian approximation machine-learning potential (GAP) to study the primary damage in silicon with close to ab initio precision level. We report detailed analysis of cascade simulations derived from our modified Si GAP, which has already shown its reliability for simulating radiation damage in silicon. Major differences in the picture of primary damage predicted by machine-learning potential compared to classical potentials are atomic mixing, defect state at the heat spike phase, defect clustering, and recrystallization rate. Atomic mixing is higher in the GAP description by a factor of two. GAP shows considerably higher number of coordination defects at the heat spike phase and the number of displaced atoms is noticeably greater in GAP. Surviving defects are dominantly isolated defects and small clusters, rather than large clusters, in GAP's prediction. The pattern by which the cascades are evolving is also different in GAP, having more expanded form compared to the locally compact form with classical potentials. Moreover, recovery of the generated defects at the heat spike phase take places with higher efficiency in GAP. We also provide the attributes of the new defect cluster that we had introduced in our previous study. A cluster of four defects, in which a central vacancy is surrounded by three split interstitials, where the surrounding atoms are all 4-folded bonded. The cluster shows higher occurrence in simulations with the GAP potential. The formation energy of the defect is 5.57 eV and it remains stable up to 700 K, at least for 30 ps. The Arrhenius equation predicts the lifetime of the cluster to be $0.0725\phantom{\rule{0.16em}{0ex}}\ensuremath{\mu}\mathrm{s}$ at room temperature.

We develop a fast and accurate machine-learned interatomic potential for the Mo-Nb-Ta-V-W quinary system and use it to study segregation and defects in the body-centered-cubic refractory high-entropy alloy MoNbTaVW. In the bulk alloy, we observe clear ordering of mainly Mo-Ta and V-W binaries at low temperatures. In damaged crystals, our simulations reveal clear segregation of vanadium, the smallest atom in the alloy, to compressed interstitial-rich regions such as radiation-induced dislocation loops. Vanadium also dominates the population of single self-interstitial atoms. In contrast, due to its larger size and low surface energy, niobium segregates to spacious regions such as the inner surfaces of voids. When annealing samples with supersaturated concentrations of defects, we find that in complete contrast to W, interstitial atoms in MoNbTaVW cluster to create only small $(\ensuremath{\sim}1 \mathrm{nm})$ experimentally invisible dislocation loops enriched by vanadium. By comparison to W, we explain this by the reduced but three-dimensional migration of interstitials, the immobility of dislocation loops, and the increased mobility of vacancies in the high-entropy alloy, which together promote defect recombination over clustering.

Structures consisting of a single Si nanodot buried within an insulating nanometric ${\mathrm{SiO}}_{2}$ layer stacked between two Si layers show promising properties for room temperature operational single-electron transistors. Moreover, such structures are highly compatible with modern complementary metal-oxide semiconductor technologies. Metastable ${\mathrm{SiO}}_{\mathrm{x}}$ phase separates into a Si nanodot and insulating, homogeneous ${\mathrm{SiO}}_{2}$ during annealing, providing a solid path towards the desired structure. However, achieving the necessary amount of excessive Si, dissolved in the ${\mathrm{SiO}}_{2}$ for correct concentrations of ${\mathrm{SiO}}_{\mathrm{x}}$, remains a technological challenge. In this work, we investigate ion-induced atom mixing in pre-built $\mathrm{Si}/{\mathrm{SiO}}_{2}/\mathrm{Si}$ nanopillars, which is considered to be a technologically promising way to produce the necessary concentrations of spatially confined ${\mathrm{SiO}}_{\mathrm{x}}$ in a controlled manner. During the high-fluence ion irradiation, we notice a significant shortening of the nanopillar and preferential loss of O atoms. Both sputtering and nanoscale ion hammering are found to be the cause of the deformation. The ion-hammering effect on nanoscale is explained by multiple small displacements, strongly enhanced after the nanopillar was rendered completely amorphous. The methods presented here can be used to determine the ion-fluence threshold for sufficient atom mixing in spatially confined regions before the large structural deformations are formed.

We present evidence of homogenization of atomic diffusion properties caused by C and N interstitials in an equiatomic single-phase high entropy alloy (FeMnNiCoCr). This phenomenon is manifested by an unexpected interstitial-induced reduction and narrowing of the directly experimentally determined migration barrier distribution of mono-vacancy defects introduced by particle irradiation. Our observation by positron annihilation spectroscopy is explained by state-of-the-art theoretical calculations that predict preferential localization of C/N interstitials in regions rich in Mn and Cr, leading to a narrowing and reduction of the mono-vacancy size distribution in the random alloy. This phenomenon is likely to have a significant impact on the mechanical behavior under irradiation, as the local variations in elemental motion have a profound effect on the solute strengthening in high entropy alloys. (C) 2021 The Authors. Published by Elsevier Ltd on behalf of Acta Materialia Inc.

${\mathrm{Ga}}_{2}{\mathrm{O}}_{3}$ is a wide-band-gap semiconductor of great interest for applications in electronics and optoelectronics. Two-dimensional (2D) ${\mathrm{Ga}}_{2}{\mathrm{O}}_{3}$ synthesized from top-down or bottom-up processes can reveal new heterogeneous structures and promising applications. In this paper, we study phase transitions among three low-energy stable ${\mathrm{Ga}}_{2}{\mathrm{O}}_{3}$ monolayer configurations using density functional theory and a machine learning Gaussian approximation potential, together with solid-state nudged elastic band calculations. Kinetic minimum energy paths involving direct atomic jump as well as concerted layer motion are investigated. The low phase transition barriers indicate feasible tunability of the phase transition and orientation via strain engineering and external electric fields. Large-scale calculations using the trained machine learning potential on the thermally activated single-atom jumps reveal the clear nucleation and growth processes of different domains. The results provide useful insights into future experimental synthesis and characterization of 2D ${\mathrm{Ga}}_{2}{\mathrm{O}}_{3}$ monolayers.

In this work, we develop a machine-learning interatomic potential for WxMo1−x random alloys. The potential is trained using the Gaussian approximation potential framework and density functional theory data produced by the Vienna ab initio simulation package. The potential focuses on properties such as elastic properties, melting, and point defects for the whole range of WxMo1−x compositions. 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.

The matrix assembly cluster source (MACS) represents a bridge between conventional instruments for cluster beam deposition (CBD) and the level of industrial production. The method is based on Ar+ ion sputtering of a pre-condensed Ar-M matrix (where M, is typically a metal such as Ag). Each Ar+ ion produces a collision cascade and thus the formation of metal clusters is in the matrix, which are then sputtered out. Here we present an experimental and computational investigation of the cluster emission process, specifically its dependence on the Ar+ ion angle of incidence and the cluster emission angle. We find the incidence angle strongly influences the emerging cluster flux, which is assigned to the spatial location of the deposited primary ion energy relative to the cluster into the matrix. We also found an approximately constant angle between the incident ion beam and the peak in the emitted cluster distribution, with value between 99° and 109°.

Highly energetic ions traversing a two-dimensional material such as graphene produce strong electronic excitations. Electrons excited to energy states above the work function can give rise to secondary electron emission, reducing the amount of energy that remains the graphene after the ion impact. Electrons can either be emitted (kinetic energy transfer) or captured by the passing ion (potential energy transfer). To elucidate this behavior that is absent in three-dimensional materials, we simulate the electron dynamics in graphene during the first femtoseconds after ion impact. We employ two conceptually different computational methods: a Monte Carlo (MC) based one, where electrons are treated as classical particles, and time-dependent density functional theory (TDDFT), where electrons are described quantum-mechanically. We observe that the linear dependence of electron emission on deposited energy, emerging from MC simulations, becomes sublinear and closer to the TDDFT values when the electrostatic interactions of emitted electrons with graphene are taken into account via complementary particle-in-cell simulations. Our TDDFT simulations show that the probability for electron capture decreases rapidly with increasing ion velocity, whereas secondary electron emission dominates in the high velocity regime. We estimate that these processes reduce the amount of energy deposited in the graphene layer by 15\,\% to 65\,\%, depending on the ion and its velocity. This finding clearly shows that electron emission must be taken into consideration when modelling damage production in two-dimensional materials under ion irradiation., 14 pages, 8 figures

GaN is the most promising upgrade to the traditional Si-based radiation-hard technologies. However, the underlying mechanisms driving its resistance are unclear, especially for strongly ionising radiation. Here, we use swift heavy ions to show that a strong recrystallisation effect induced by the ions is the key mechanism behind the observed resistance. We use atomistic simulations to examine and predict the damage evolution. These show that the recrystallisation lowers the expected damage levels significantly and has strong implications when studying high fluences for which numerous overlaps occur. Moreover, the simulations reveal structures such as point and extended defects, density gradients and voids with excellent agreement between simulation and experiment. We expect that the developed modelling scheme will contribute to improving the design and test of future radiation-resistant GaN-based devices. Gallium nitride is a wide bandgap semiconductor which is generally expected to replace some silicon-based technologies, despite some of its properties still requiring further investigation. Here, using a two-temperature model coupled to molecular dynamics simulations, the authors investigate and predict the effects of strongly ionising radiation in gallium nitride, revealing the mechanism behind its unusual resistance to radiation.

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. (c) 2020 The Author(s). Published by Elsevier Ltd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).

Nanomaterials undergoing cyclic swelling-deswelling benefit from inner void spaces that help accommodate significant volumetric changes. Such flexibility, however, typically comes at a price of reduced mechanical stability, which leads to component deterioration and, eventually, failure. Here, we identify an optimised building block for silicon-based lithium-ion battery (LIB) anodes, fabricate it with a ligand- and effluent-free cluster beam deposition method, and investigate its robustness by atomistic computer simulations. A columnar amorphous-silicon film was grown on a tantalum-nanoparticle scaffold due to its shadowing effect. PeakForce quantitative nanomechanical mapping revealed a critical change in mechanical behaviour when columns touched forming a vaulted structure. The resulting maximisation of measured elastic modulus (similar to 120GPa) is ascribed to arch action, a well-known civil engineering concept. The vaulted nanostructure displays a sealed surface resistant to deformation that results in reduced electrode-electrolyte interface and increased Coulombic efficiency. More importantly, its vertical repetition in a double-layered aqueduct-like structure improves both the capacity retention and Coulombic efficiency of the LIB. Lithiation of anodes during cycling of lithium-ion batteries generates stresses that reduce operation lifetime. Here, a composite silicon-based anode with a nanoscale vaulted architecture shows high mechanical stability and electrochemical performance in a lithium-ion battery., Communications Materials, 2 (1), ISSN:2662-4443

As a promising material used in accelerators and in space in the future, it is important to study the property and structural changes of graphene and diamond-like carbon on the surface as a protective layer before and after swift heavy ion irradiation, although this layer could have a loose structure due to the intrinsic sp(2) surrounding environment of graphene during its deposition period. In this study, by utilizing inelastic thermal spike model and molecular dynamics, we simulated swift heavy ion irradiation and examined the track radius in the vertical direction, as well as temperature, density, and sp(3) fraction distribution along the radius from the irradiation center at different time after irradiation. The temperature in the irradiation center can reach over 11000 K at the beginning of irradiation while there would be a low density and sp(3) fraction area left in the central region after 100 ps. Ring analysis also demonstrated a more chaotic cylindrical region in the center after irradiation. After comprehensive consideration, diamond-like carbon deposited by 70 eV carbon bombardment provided the best protection.

We develop a silicon Gaussian approximation machine learning potential suitable for radiation effects, and use it for the first ab initio simulation of primary damage and evolution of collision cascades. The model reliability is confirmed by good reproduction of experimentally measured threshold displacement energies and sputtering yields. We find that clustering and recrystallization of radiation-induced defects, propagation pattern of cascades, and coordination defects in the heat spike phase show striking differences to the widely used analytical potentials. The results reveal that small defect clusters are predominant and show new defect structures such as a vacancy surrounded by three interstitials. Impact statement Quantum-mechanical level of accuracy in simulation of primary damage was achieved by a silicon machine learning potential. The results show quantitative and qualitative differences from the damage predicted by any previous models.

Kinetic Monte Carlo (KMC) is a powerful method for simulation of diffusion processes in various systems. The accuracy of the method, however, relies on the extent of details used for the parameterization of the model. Migration barriers are often used to describe diffusion on atomic scale, but the full set of these barriers may become easily unmanageable in materials with increased chemical complexity or a large number of defects. This work is a feasibility study for applying a machine learning approach for Cu surface diffusion. We train an artificial neural network on a subset of the large set of 2 26 barriers needed to correctly describe the surface diffusion in Cu. Our KMC simulations using the obtained barrier predictor show sufficient accuracy in modelling processes on the low-index surfaces and display the correct thermodynamical stability of these surfaces.

We develop a set of machine-learning interatomic potentials for elemental V, Nb, Mo, Ta, and W using the Gaussian approximation potential framework. The potentials show good accuracy and transferability for elastic, thermal, liquid, defect, and surface properties. All potentials are augmented with accurate repulsive potentials, making them applicable to radiation damage simulations involving high-energy collisions. We study melting and liquid properties in detail and use the potentials to provide melting curves up to 400 GPa for all five elements.

As Rutherford backscattering spectrometry in channeling mode (RBS/C) is an efficient technique for characterizing crystallographic defects, its computational simulation has drawn attention over the past several decades. Recently, a RBS/C simulation code based on the binary collision approximation called Rutherford backscattering simulation in arbitrary defective crystals has been suggested and successfully applied to predict the RBS/C spectra from different damaged materials, whose structures were generated in high-dose ion irradiation atomistic simulations. In the present paper, we introduce new developments improving the flexibility of the developed software and its applicability to different types of materials. More precisely, we modified the algorithm describing the slowdown process of backscattered ions, added fitting parameters in the collision partner search routine, modified the routine taking into account target atom thermal vibrations and provided new descriptions of the ion beam divergence. As an example, the effect of the modifications on simulated RBS/C spectra is shown for an 〈011〉-oriented UO2 crystal analyzed with a 3.085 MeV He2+ ion beam. Some of these changes proved necessary to achieve satisfying agreement between simulations and experimental data. Similar observation was made for 〈001〉-oriented Si and 〈001〉-oriented GaAs crystals analyzed with a 1.4 MeV He+ ion beam. In these simulations, the modifications have also resulted in good agreement with experiment.

This review concentrates on the specific properties and characteristics of damage structures generated with high-energy ions in the electronic energy loss regime. Irradiation experiments with so-called swift heavy ions (SHI) find applications in many different fields, with examples presented in ion-track nanotechnology, radiation hardness analysis of functional materials, and laboratory tests of cosmic radiation. The basics of the SHI-solid interaction are described with special attention to processes in the electronic subsystem. The broad spectrum of damage phenomena is exemplified for various materials and material classes, along with a description of typical characterization techniques. The review also presents state-of-the-art modeling efforts that try to account for the complexity of the coupled processes of the electronic and atomic subsystems. Finally, the relevance of SHI phenomena for effects induced by fission fragments in nuclear fuels and how this knowledge can be applied to better estimate damage risks in nuclear materials is discussed.

Nanoparticles (NPs), as the most prototypical functional building blocks in nanoscience, exhibit size-, shape-, composition-, and structure-dependent behavior which is different from the corresponding bulk materials. Arguably, the structures and properties of NPs cannot be understood purely from experimental data. Deeper insights can be gained by complementary theoretical or computational modeling. This chapter presents an introduction to simulations of metallic and semiconductor NPs in inert environment using multiscale computational modeling techniques, including density functional theory, classical molecular dynamics, and Monte Carlo methods. We review relevant results obtained with such simulations in the field of cluster beam deposition and comment on several challenges that need to be addressed in future.

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.

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. Keywords: Copper, Iron, Kinetic Monte Carlo, Surface diffusion, Rigid lattice, Migration barriers, Atomic jumps

High electric fields are present in a rapidly growing number of applications, which include elementary particle accelerators, vacuum interrupters, miniature x-ray sources, and satellites. Many of these applications are limited by the breakdown strength of the materials exposed to electric fields. Different methods have been developed to improve the quality of metal electrode surfaces, aiming to increase their breakdown strength. Not many systematical studies have been performed to provide a proper understanding of what contributes to the correlation between the breakdown strength and the quality of the surface. In this work, we apply a novel method for reducing vacuum arc breakdowns by cleaning the electrode surfaces with O and Ar plasma. The method can be used to alter the surfaces of the Cu electrodes in situ, i.e., without exposing them to air between the measurements. This plasma cleaning treatment is shown to reduce the number of surface impurities and to speed up the conditioning process of the samples under high-voltage pulses. Specifically, the first breakdown field was observed to increase by more than 90% after the plasma cleaning.

The effect of noble gas cluster species on the cluster interaction with solid surfaces was investigated. Processes of Ar, Kr and Xe clusters interaction with Cu and Mo surfaces were studied using molecular dynamics simulations. It is shown that lighter cluster front atoms undergo more backscattering from surface atoms, causing more intense multiple collisions between cluster atoms. This affects cluster penetration, energy exchange between the cluster and surface atoms, and cluster thermalization. The influence of energy per cluster atom on these effects is discussed. The effect of noble gas cluster species on the cluster interaction with solid surfaces was investigated. Processes of Ar, Kr and Xe clusters interaction with Cu and Mo surfaces were studied using molecular dynamics simulations. It is shown that lighter cluster front atoms undergo more backscattering from surface atoms, causing more intense multiple collisions between cluster atoms. This affects cluster penetration, energy exchange between the cluster and surface atoms, and cluster thermalization. The influence of energy per cluster atom on these effects is discussed.

Multiprincipally designed concentrated solid solution alloys, such as high entropy alloys (HEA) and equiatomic multi-component alloys (EAMC-alloys) have shown much promise for use as structural components in future nuclear energy production concepts. The irradiation tolerance in these novel alloys has been shown to be superior to that in more conventional metals used in current nuclear reactors. However, studies involving irradiation of HEAs and EAMC-alloys have usually been performed at room temperature. Hence, in this study the irradiation damage is investigated computationally in two different Ni-based EAMC-alloys and pure Ni at four different temperatures, ranging from 138 K to 800 K. The irradiation damage was studied by analyzing point defects, defect cluster sizes and dislocation networks in the materials. Dislocation loop mobility calculations were performed to help understanding the formation of different dislocation networks in the irradiated materials. Utilizing the knowledge of the depth distribution of damage, and using simulations of Rutherford backscattering in channeling conditions (RBS/c), we can relate our results to experimental data. The main findings are that the alloys have superior irradiation tolerance at all temperatures as compared to pure Ni, and that the damage is reduced in all materials with an increase in temperature.

We develop a new method using binary collision approximation simulating the Rutherford backscattering spectrometry in channeling conditions (RBS/C) from molecular dynamics atom coordinates of irradiated cells. The approach allows comparing experimental and simulated RBS/C signals as a function of depth without fitting parameters. The simulated RBS/C spectra of irradiated Ni and concentrated solid solution alloys (CSAs, NiFe and NiCoCr) show a good agreement with the experimental results. The good agreement indicates the damage evolution under damage overlap conditions in Ni and CSAs at room temperature is dominated by defect recombination and migration induced by irradiation rather than activated thermally.

Volume: 406 Host publication title: Nuclear Instruments and Methods in Physics Research Section B: Beam Interactions with Materials and Atoms The results of molecular dynamics simulations of the bombardment of the Cu (100) and Mo (100) single-crystals by 10 keV Ar cluster ions of different sizes are presented in this paper. Spatial distributions of sputtered material were calculated. The anisotropy of the angular distributions of sputtered atoms was revealed. It was found that the character of the anisotropy is different for Cu and Mo targets. The reasons leading to this anisotropy are discussed according to the dependences of the angular distributions on the cluster size and on the target material.

The structure of heterogeneous nanocatalysts supported on metal oxide materials and their morphological changes during oxidation/reduction processes play a crucial role in determining the resulting catalytic activity. Herein, we study the thermal oxidation mechanism of Pd nanoparticles supported on CuO nanowires by combining in situ environmental transmission electron microscopy (TEM), ex situ experiments, and ab initio density functional theory (DFT) calculations. High-resolution TEM imaging assisted by geometric phase analysis enabled the analysis of partially oxidized, fully oxidized, and distinct onion-like Pd nanoparticles with subsurface dislocations. Furthermore, preferential crystalline orientations between PdO nanoparticles and the CuO nanowire support have been found. Hence, the CuO–Pd interface is crucial for the thermal oxidation of Pd nanoparticles, as corroborated by electron energy loss spectroscopy and DFT calculations. The latter revealed a considerably lower energy barrier for penetratio...

This article has an erratum: DOI 10.1016/j.carbon.2017.03.065 We examine swift heavy ion-induced defect production in suspended single layer graphene using Raman spectroscopy and a two temperature molecular dynamics model that couples the ionic and electronic subsystems. We show that an increase in the electronic stopping power of the ion results in an increase in the size of the pore-type defects, with a defect formation threshold at 1.22–1.48 keV/layer. We also report calculations of the specific electronic heat capacity of graphene with different chemical potentials and discuss the electronic thermal conductivity of graphene at high electronic temperatures, suggesting a value in the range of 1 Wm−1 K−1. These results indicate that swift heavy ions can create nanopores in graphene, and that their size can be tuned between 1 and 4 nm diameter by choosing a suitable stopping power.

In this work we combine density functional theory and quantum transport calculations to study the influence of atomic--scale defects on the work function and field emission characteristics of metal surfaces. We develop a general methodology for the calculation of the field emitted current density from nano-featured surfaces, which is then used to study specific defects on a Cu(111) surface. Our results show that the inclusion of a defect can significantly locally enhance the field emitted current density. However, this increase is attributed solely to the decrease of the work function due to the defect, with the effective field enhancement being minute. Finally, the Fowler--Nordheim equation is found to be valid when the modified value for the work function is used, with only an approximately constant factor separating the computed currents from those predicted by the Fowler--Nordheim equation., Comment: 12 pages, 9 figures

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.

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.

International audience; The elongation process under swift heavy ion irradiation (74 MeV Kr ions) of gold NPs, with a diameter in the range 10–30 nm, and embedded in a silica matrix has been investigated by combining experiment and simulation techniques: three-dimensional thermal spike (3DTS), molecular dynamics (MD) and a phenomenological simulation code specially developed for this study. 3DTS simulations evidence the formation of a track in the host matrix and the melting of the NP after the passage of the impinging ion. MD simulations demonstrate that melted NPs have enough time to expand after each ion impact. Our phenomenological simulation relies on the expansion of the melted NP, which flows in the track in silica with modified (lower) density, followed by its recrystallization upon cooling. Finally, the elongation of the spherical NP into a cylindrical one, with a length proportional to its initial size and a width close to the diameter of the track, is the result of the superposition of the independent effects of each expansion/recrystallization process occurring for each ion impact. In agreement with experiment, the simulation shows the gradual elongation of spherical NPs in the ion-beam direction until their widths saturate in the steady state and reach a value close to the track diameter. Moreover, the simulations indicate that the expansion of the gold NP is incomplete at each ion impact.

Combining classical electrodynamics and density functional theory (DFT) calculations, we develop a general and rigorous theoretical framework that describes the energetics of metal surfaces under high electric fields. We show that the behavior of a surface atom in the presence of an electric field can be described by the polarization characteristics of the permanent and field-induced charges in its vicinity. We use DFT calculations for the case of a W adatom on a W{110} surface to confirm the predictions of our theory and quantify its system-specific parameters. Our quantitative predictions for the diffusion of W-on-W{110} under field are in good agreement with experimental measurements. This work is a crucial step towards developing atomistic computational models of such systems for long-term simulations., 9 pages, 5 figures, 2 tables

To this day, engineering nanoalloys beyond bimetallic compositions has scarcely been within the scope of physical deposition methods due to the complex, nonequilibrium processes they entail. Here, we report a gas-phase synthesis strategy for the growth of multimetallic nanoparticles: magnetron-sputtering inert-gas condensation from neighboring monoelemental targets provides the necessary compositional flexibility, whereas in-depth atomistic computer simulations elucidate the fast kinetics of nucleation and growth that determines the resultant structures. We fabricated consistently trimetallic Au–Pt–Pd nanoparticles, a system of major importance for heterogeneous catalysis applications. Using high-resolution transmission electron microscopy, we established their physical and chemical ordering: Au/Pt-rich core@Pd-shell atomic arrangements were identified for particles containing substantial amounts of all elements. Decomposing the growth process into basic steps by molecular dynamics simulations, we identified a fundamental difference between Au/Pt and Pd growth dynamics: Au/Pt electronic arrangements favor the formation of dimer nuclei instead of larger-size clusters, thus significantly slowing down their growth rate. Consequently, larger Pd particles formed considerably faster and incorporated small Au and Pt clusters by means of in-flight decoration and coalescence. A broad range of icosahedral, truncated-octahedral, and spheroidal face-centered cubic trimetallic nanoparticles were reproduced in simulations, in good agreement with experimental particles. Comparing them with their expected equilibrium structures obtained by Monte Carlo simulations, we identified the particles as metastable, due to out-of-equilibrium growth conditions. We aspire that our in-depth study will constitute a significant advance toward establishing gas-phase aggregation as a standard method for the fabrication of complex nanoparticles by design.

In search of materials with better properties, polycrystalline materials are often found to be superior to their respective single crystalline counterparts. Reduction of grain size in polycrystalline materials can drastically alter the properties of materials. When the grain sizes reach the nanometer scale, the improved mechanical response of the materials make them attractive in many applications. Multicomponent solid-solution alloys have shown to have a higher radiation tolerance compared with pure materials. Combining these advantages, we investigate the radiation tolerance of nanocrystalline multicomponent alloys. We find that these alloys withstand a much higher irradiation dose, compared with nanocrystalline Ni, before the nanocrystallinity is lost. Some of the investigated alloys managed to keep their nanocrystallinity for twice the irradiation dose as pure Ni.

We have calculated the migration barriers for surface diffusion on Tungsten. Our results form a self-sufficient parameterization for Kinetic Monte Carlo simulations of arbitrarily rough atomic tungsten surfaces, as well as nanostructures such as nanotips and nanoclusters. The parameterization includes first- and second-nearest neighbour atom jump processes, as well as a third-nearest neighbour exchange process. The migration energy barriers of all processes are calculated with the Nudged Elastic Band method. The same attempt frequency for all processes is found sufficient and the value is fitted to Molecular Dynamics simulations. The model is validated by correctly simulating with Kinetic Monte Carlo the energetically favourable W nanocluster shapes, in good agreement with Molecular Dynamics simulations.

Structure damage formation in GaN under light P and heavy Ag monatomic and small molecular PF4 ions is studied by RBS/C and classical molecular dynamics (MD) simulations. Molecules are found to be most efficient in surface amorphization, whereas in the sample bulk Ag ions produce more damage than others. Cumulative MD simulations reveal nonlinear increase of big defect cluster generation in dense collision cascades formed by molecules at the surface vicinity and along most part of Ag ion path. Creation of these big defect clusters intensifies all processes responsible for stable damage formation, in particular, it is one of the reasons of experimentally observed peculiarities of damage production.

Variability in the short-intermediate range order of pure amorphous Si synthesized by different experimental and computational techniques is probed by measuring mass density, atomic coordination, bond-angle deviation, and dihedral angle deviation. It is found that there is significant variability in order parameters at these length scales in this archetypal covalently bonded, monoatomic system. This diversity strongly reflects preparation method and thermal history in both experimental and simulated systems. Where experiment and simulation do not quantitatively agree, this is partly due to inherent differences in analysis and time scales. Relaxed forms of amorphous Si quantitatively match continuous random networks generated by a hybrid method of bond-switching Monte Carlo and molecular dynamics simulation. Qualitative trends were identified in other experimental and computed forms of a-Si. Ion-implanted a-Si′s are less ordered than the relaxed forms. Preparation methods which narrowly avoid crystallization such as experimental pressure-induced amorphization or simulated melt-quenching result in the most disordered structures. As no unique form of amorphous Si exists, there can be no single model for the material.

Gaseous nitrogen is planned to be used as a seeding species to control the power flux in future fusion reactors with ITER-like divertors. Nitrogen interacts with the first wall materials, particularly with tungsten, leading to sputtering and changes of chemical composition of the material. We use the molecular dynamics methods with a recently developed WN potential to analyze the mechanisms leading to these modifications. We performed the simulations of cumulative nitrogen irradiation runs of tungsten surface. The sputtering yields obtained in our cumulative runs are in good agreement with experimental data. We observe the decrease of the tungsten sputtering yield with nitrogen accumulation and determine the reasons for the observed trend. The cluster analysis reveals the composition of the sputtered particles, suggesting the swift chemical sputtering process that occurs under the prolonged nitrogen irradiation of tungsten. We also observe and analyze the nitrogen saturation in the temperature range below the thermal stability limit. (C) 2020 Elsevier B.V. All rights reserved.

Diffusion bonding of copper disks is an important step during the assembly of accelerating structures -the main components of power radio-frequency linear accelerators-. During the diffusion bonding copper disks are subjected to pressure at high temperatures. Finding the optimal combination of pressure and temperature will enable an accurate design of manufacturing workflow and machining tolerances. However, required optimization is not possible without good understanding of physical processes developed in copper under pressure and high temperature. In this work, the combined effect of temperature and pressure on closing time of inter-granular voids is examined by means of molecular dynamics simulations. In particular, a nano-void of 3.5–5.5 nm in diameter representing a peak and a valley of surface roughness facing each other was inserted between identical copper grains. The simulations performed at T = 1250 K, the temperature used in experimental condition, and the 300–800 MPa pressure range indicated the dislocation-mediated enhancement of atomic diffusion leading to full void closure.

Two-dimensional molybdenum-disulfide (MoS2) catlysts 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 controlled creation of sulfur vacancies. Here, we report a novel method of activating the MoS2 surface in this respect using swift heavy ion irradiation. The creation of nanometer-scale structures by the 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 enhance of the electrochemical current density by over 160% as compared to an identical but non-irradiated MoS2 surface.

When a swift heavy ion (SHI) penetrates amorphous $\mathrm{Si}{\mathrm{O}}_{2}$, a core/shell (C/S) ion track is formed, which consists of a lower-density core and a higher-density shell. According to the conventional inelastic thermal spike (iTS) model represented by a pair of coupled heat equations, the C/S tracks are believed to form via ``vaporization'' and melting of the $\mathrm{Si}{\mathrm{O}}_{2}$ induced by SHI (V-M model). However, the model does not describe what the vaporization in confined ion-track geometry with a condensed matter density is. Here we reexamine this hypothesis. While the total and core radii of the C/S tracks determined by small angle x-ray scattering are in good agreement with the vaporization and melting radii calculated from the conventional iTS model under high electronic stopping power $({S}_{e})$ irradiations (g10 keV/nm), the deviations between them are evident at low-${S}_{e}$ irradiation (3--5 keV/nm). Even though the iTS calculations exclude the vaporization of $\mathrm{Si}{\mathrm{O}}_{2}$ at the low ${S}_{e}$, both the formation of the C/S tracks and the ion shaping of nanoparticles (NPs) are experimentally confirmed, indicating the inconsistency with the V-M model. Molecular dynamics (MD) simulations based on the two-temperature model, which is an atomic-level modeling extension of the conventional iTS, clarified that the ``vaporlike'' phase exists at ${S}_{e}\ensuremath{\sim}5$ keV/nm or higher as a nonequilibrium phase where atoms have higher kinetic energies than the vaporization energy, but are confined at a nearly condensed matter density. Simultaneously, the simulations indicate that the vaporization is not induced under 50-MeV Si irradiation $({S}_{e}\ensuremath{\sim}3$ keV/nm), but the C/S tracks and the ion shaping of nanoparticles are nevertheless induced. Even though the final density variations in the C/S tracks are very small at the low stopping power values (both in the simulations and experiments), the MD simulations show that the ion shaping can be explained by flow of liquid metal from the NP into the transient low-density phase of the track core during the first \ensuremath{\sim}10 ps after the ion impact. The ion shaping correlates with the recovery process of the silica matrix after emitting a pressure wave. Thus, the vaporization is not a prerequisite for the C/S tracks and the ion shaping.

We propose a method for efficiently coupling the finite element method with atomistic simulations, while using molecular dynamics or kinetic Monte Carlo techniques. Our method can dynamically build an optimized unstructured mesh that follows the geometry defined by atomistic data. On this mesh, different multiphysics problems can be solved to obtain distributions of physical quantities of interest, which can be fed back to the atomistic system. The simulation flow is optimized to maximize computational efficiency while maintaining good accuracy. This is achieved by providing the modules for a) optimization of the density of the generated mesh according to requirements of a specific geometry and b) efficient extension of the finite element domain without a need to extend the atomistic one. Our method is organized as an open-source C++ code. In the current implementation, an efficient Laplace equation solver for calculation of electric field distribution near rough atomistic surface demonstrates the capability of the suggested approach., 25 pages, 14 figures

The effect of low energy irradiation, where the sputtering is imperceptible, has not been deeply studied in the pattern formation. In this work, we want to address this question by analyzing the nanoscale topography formation on a Si surface, which is irradiated at room temperature by Arthorn ions near the displacement threshold energy, for incidence angles ranging from 0 degrees to 85 degrees. The transition from the smooth to ripple patterned surface, i.e., the stability/instability bifurcation angle is observed at 55 degrees, whereas the ripples with their wave-vector is parallel to the ion beam projection in the angular window of 60 degrees-70 degrees, and with 90 degrees rotation with respect to the ion beam projection at the grazing angles of incidence. A similar irradiation setup has been simulated by means of molecular dynamics, which made it possible, first, to quantify the effect of the irradiation in terms of erosion and redistribution using sequential irradiation and, second, to evaluate the ripple wavelength using the crater function formalism. The ripple formation results can be solely attributed to the mass redistribution based mechanism, as erosion due to ion sputtering near or above the threshold energy is practically negligible. Published by AIP Publishing.

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.

Stable C-C bonds existing in several sp hybridizations place carbon thin films of different structural compositions among the materials most tolerant to radiation damage, for applications in extreme environments. One of such applications, solid state electron stripper foils for heavy-ion accelerators, requires the understanding of the structural changes induced by high-energy ion irradiation. Tolerance of carbon structure to radiation damage, thermal effects and stress waves due to swift heavy ion impacts defines the lifetime and operational efficiency of the foils. In this work, we analyze the consequences of a single swift heavy ion impact on two different amorphous carbon structures by means of molecular dynamic simulations. The structures are constructed by using two different recipes to exclude the correlation of the evolution of sp2-to-sp3 hybridization with the initial condition. Both initial structures contain approximately 60% of sp2-bonded carbon atoms, however, with different degree of clustering of atoms with sp3 hybridization. We simulate the swift heavy ion impact employing an instantaneous inelastic thermal spike model. The analysis of changes in density, bonding content and the number and size of carbon primitive rings reveals graphitization of the material within the ion track, with higher degree of disorder in the core and more order in the outer shell. Simulated track dimensions are comparable to those observed in small angle x-ray scattering measurements of evaporation-deposited amorphous carbon stripper foils irradiated by 1.14 GeV U ions.