Search

The off-normal ion irradiation of semiconductor materials is seen to induce nanopatterning effects. Different theories are proposed to explain the mechanisms that drive self-reorganization of amorphizable surfaces. One of the prominent hypothesis associates formation of nanopatterning with the changes of sputtering characteristics caused by changes in surface morphology. At ultralow energy, when sputtering is negligible, the Si surface has still been seen to reorganize forming surface ripples with the wave vector is either aligned with the ion beam direction or perpendicular to it. In this work, we investigate the formation of ripples using molecular dynamics in all the three regimes of ripple formation: low angles where no ripples form, intermediate regime where the ripple wave vectors are parallel to the beam, and high angles where they are perpendicular to it. We obtain atom-level insight on how the ion-beam driven atomic dynamics at the surface contributes to organization, or lack of it, in all the different regimes. Results of our simulations agree well with experimental observations in the same range of ultralow energy of ion irradiation.

Interaction potentials were obtained by the density functional theory (DFT) and nuclear stopping powers (NSP) were calculated for 48 systems in the energy range above 10 eV. It was shown that NSP calculated using the DFT potentials in the collision energy range of 10–1000 eV give more accurate values comparing with the SRIM data, obtained data differs from SRIM data by 15–70%. The presence of a potential well leads to the emergence of an additional NSP peak at low energies. Comparison of classical calculations of the transport cross section with semiclassical ones showed their identity at energies of up to 1 eV. The criterion for the applicability of classical calculations for the transport cross section and NSP cross sections is the condition l>1 (l is the angular momentum). The importance of including multichannel scattering in NSP calculations was demonstrated, for the case of energies below 20 eV.

Ga2O3 is a wide-bandgap semiconductor of emergent importance for applications in electronics and optoelectronics. However, vital information of the properties of complex coexisting Ga2O3 polymorphs and low-symmetry disordered structures is missing. In this work, we develop two types of kernel-based machine-learning Gaussian approximation potentials (ML-GAPs) for Ga2O3 with high accuracy for β/κ/α/δ/γ polymorphs and universal generality for disordered structures. We release two versions of interatomic potentials in parallel, namely soapGAP and tabGAP, for excellent accuracy and exceeding speedup, respectively. We systematically show that both the soapGAP and tabGAP can reproduce the structural properties of all the five polymorphs in an exceptional agreement with ab initio results, meanwhile boost the computational efficiency with 5×102 and 2×105 computing speed increases compared to density functional theory, respectively. The results show that the liquid-solid phase transition proceeds in three different stages, a "slow transition", "fast transition", and "only Ga migration". We show that this complex dynamics can be understood in terms of distinct behavior of O and Ga sublattices in the interfacial layer.

With full knowledge of a material's atomistic structure, it is possible to predict any macroscopic property of interest. In practice, this is hindered by limitations of the chosen characterisation techniques. For example, electron microscopy is unable to detect the smallest and most numerous defects in irradiated materials. Instead of spatial characterisation, we propose to detect and quantify defects through their excess energy. Differential scanning calorimetry (DSC) of irradiated Ti measures defect densities 5 times greater than those determined using transmission electron microscopy (TEM). Our experiments also reveal two energetically-distinct processes where the established annealing model predicts one. Molecular dynamics (MD) simulations discover the defects responsible and inform a new mechanism for the recovery of irradiation-induced defects. The combination of annealing experiments and simulations can reveal defects hidden to other characterisation techniques, and has the potential to uncover new mechanisms behind the evolution of defects in materials., Comment: main: 17 pages and 6 figures, supplemental: 25 pages and 16 figures

Nanostructured tungsten has been proposed as a promising option for plasma facing materials in future fusion reactors, because compared to conventional tungsten it shows advantages such as a better radiation resistance and, in particular, a retardation of tungsten-fuzz growth. Besides these aspects, the sputtering yield of nanostructured tungsten under ion bombardment is of interest, since it would affect the atomic density of tungsten emitted into the fusion plasma, which leads to radiative heat losses. In this work, we present a multiscale approach for investigating the sputtering yield of nanocolumnar tungsten surfaces under 1 keV and 2 keV Ar irradiation. Our results cover experiments and also computational simulations, which operate either on the basis of the binary collision approximation and ray tracing or use a full molecular dynamics implementation. In our studied case, both computational approaches can predict the sputtering yield of nanocolumnar tungsten surfaces very well. In comparison to flat W, we observe a much reduced dependence on the ion incidence angle, similar as reported for conventional rough surfaces in literature. However, an additional global reduction of the sputtering yield was identified, which can be attributed to geometrical redeposition effects between the separated nanocolumns. These results support the applicability of nanocolumnar tungsten as a first wall coating.

Swift heavy ion (SHI)-induced shape modification of metal nanoparticles (NPs) embedded in an insulating matrix has been reported in many experimental studies. The shaping process was studied theoretically by modeling transport of the heat generated by electron excitations during a SHI impact on the embedded NP. These models have assumed that the interface between the matrix and the metal does not alter the heat flow. However, the difference between the Fermi level of the metal and the bottom of the conduction band in the insulator may result in a significant energy barrier that obstructs the free flow of the heat carried by energetic electrons. Moreover, the interface may enhance electron-lattice scattering and resist lattice heat conduction. In this work, we use the finite-element method to solve partial differential equations for heat conduction through the interface between the metal NP and the insulating matrix including interface effects. Based on an exemplary case of a gold NP embedded in a silica matrix, we study how the processes at the interface may alter the heat transport through it. We observe that obstruction at the interface impacts mainly the timescale and efficiency of material melting. Each of the studied effects changes the size and shape of the NP regions, where the temperature rises above the melting point. Understanding the role of the interface on heat dynamics during SHI impacts can improve estimations of the maximal size of embedded NPs that are still susceptible to shape modification by energetic ions. The accuracy of model predictions can be crucial for the development of nanoscale optoelectronic applications.

In spite of remarkable developments in the field of advanced materials, silicon remains one of the foremost semiconductors of the day. Of enduring relevance to science and technology is silicon's nanomechanical behaviour including phase transformation, amorphization and dislocations generation, particularly in the context of molecular dynamics and materials research. So far, comprehensive modelling of the whole cycle of events in silicon during nanoscale deformation has not been possible, however, due to the limitations inherent in the existing interatomic potentials. This paper examines how well an unconventional combination of two well-known potentials - the Tersoff and Stillinger-Weber - can perform in simulating that complexity. Our model indicates that an irreversible deformation of silicon (Si-I) is set in motion by a transformation to a non-diamond structure (Si-nd), and followed by a subsequent transition to the Si-II and Si-XII' phases (Si-I->Si-nd->Si-II->Si-XII'). This leads to the generation of dislocations spreading outwards from the incubation zone. In effect, our simulations parallel each and every one of the structural changes detected experimentally in the deformed material. This includes both the sequence of phase transitions and dislocation activity, which - taken together - neither the Tersoff nor Stillinger-Weber, or indeed any other available Si interatomic potential, is able to achieve in its own right. We have sought to additionally validate our method of merging atomic potentials by applying it to germanium, and found it can equally well predict germanium's transformation from a liquid to amorphous state., 35 pages, 10 figures

We use molecular dynamics (MD) simulation with numerical characterisation and statistical analysis to study the mechanisms of damage evolution and p-type doping efficiency by aluminum (Al) ion implantation into 3C silicon carbide (SiC) with subsequent annealing. By incorporating the electronic stopping power for implantation, a more accurate description of the atomic-scale mechanisms of damage evolution and distribution in SiC can be obtained. The simulation results show a novel observation that the recrystallization process occurs in the region below the subsurface layer, and develops from amorphous-crystalline interface to the damage center region, which is a new insight into previously published studies. During surface recrystallization, significant compressive stress concentration occurs, and more structural phase transition atoms and dislocations formed at the damage-rich-crystalline interface. Another point of interest is that for low-dose implantation, more implantation-induced defects hamper the doping efficiency. Correspondingly, the correlation between lattice damage and doping efficiency becomes weaker as the implant dose increases under the same annealing conditions. Our simulation also predicts that annealing after high temperature (HT) implantation is more likely to lead to the formation of carbon vacancies (V-C).

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.

Highly energetic ions have been previously used to modify the shape of metal nanoparticles embedded in an insulating matrix. In this work, we demonstrate that under suitable conditions, energetic ions can be used not only for shape modification but also for manipulation of nanorod orientation. This observation is made by imaging the same nanorod before and after swift heavy ion irradiation using a transmission electron microscope. Atomistic simulations reveal a complex mechanism of nanorod re-orientation by an incremental change in its shape from a rod to a spheroid and further back into a rod aligned with the beam. Highly energetic ions have been previously used to modify the shape of metal nanoparticles embedded in an insulating matrix. In this work, we demonstrate that under suitable conditions, energetic ions can be used not only for shape modification but also for manipulation of nanorod orientation. This observation is made by imaging the same nanorod before and after swift heavy ion irradiation using a transmission electron microscope. Atomistic simulations reveal a complex mechanism of nanorod re-orientation by an incremental change in its shape from a rod to a spheroid and further back into a rod aligned with the beam. Published under an exclusive license by AIP Publishing.

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.

The Gaussian approximation potential (GAP) is an accurate machine-learning interatomic potential that was recently extended to include the description of radiation effects. In this study, we seek to validate a faster version of GAP, known as tabulated GAP (tabGAP), by modelling primary radiation damage in 50- 50 W-Mo alloys and pure W using classical molecular dynamics. We find that W-Mo exhibits a similar number of surviving defects as in pure W. We also observe W-Mo to possess both more efficient recom-bination of defects produced during the initial phase of the cascades, and in some cases, unlike pure W, recombination of all defects after the cascades cooled down. Furthermore, we observe that the tabGAP is two orders of magnitude faster than GAP, but produces a comparable number of surviving defects and cluster sizes. A small difference is noted in the fraction of interstitials that are bound into clusters.(c) 2023 The Author(s). Published by Elsevier B.V. This is an open access article under the CC BY license ( http://creativecommons.org/licenses/by/4.0/ )

The response of Rutherford backscattering spectrometry in channeling mode through a dechanneling mechanism to the presence of voids in crystals has been considered to be qualitatively weak. However there is a lack of the validation of its quantitative behavior. In this work, we present an investigation on the dechanneling induced by voids with different shapes in tungsten based on a simulation approach. We observe that dechanneling cross section of large voids is indeed found as a product of the minimum yield and the area projected from the void to the target surface as suggested by analytical models in literature. However, this method overestimates the dechanneling induced by small voids, in which the spatial distribution of incident ions inside a target has a non-negligible effect. We found that an inter-void distance effect is able to further lower dechanneling signals if the inter-void distance is small. When small spherical voids coalesce into a group of larger ones, the dechanneling fraction is not expected to increase. In addition, comparisons between voids and stacking faults show that there are significant discrepancies between these two defects in terms of dechanneling.

Nuclear fusion is one of the most promising concepts for future energy production, due to the almost endless source of fuel and the lack of greenhouse effects during operation. However, to successfully build a fusion reactor, the development of new materials and knowledge of their behavior are needed. One important structural part of the reactor and the reactor vessel is the wall facing the plasma. The wall will be bombarded by the products of the nuclear reaction, which will erode and degrade its performance. In this work, we study the sputtering of different tungsten surfaces under various conditions, obtaining a deeper understanding of the process using molecular dynamics simulations. Additionally, we present the evolution of W fuzz cells and the effect of surface feature height on the erosion and sputtering of the surfaces under ion irradiation.

An excess of events of unknown origin at low energies below 1 keV has been observed in multiple low-threshold dark matter detectors. Depending on the target material, nuclear recoil events at these energies may cause lattice defects, in which case a part of the true recoil energy is stored in the defect and not observed in the phonon detector. If the threshold for defect creation is sharp, this effect leads to a prominent feature in the observed recoil spectrum. Electronic recoils at low energies do not create defects and therefore the feature in the observed spectrum is not expected in that case. We propose to use the sharp defect creation threshold of diamond to test if the low energy events are due to nuclear recoils. Based on simulated data we expect the nuclear recoil bump in the observed spectrum to be visible in diamond with just ~0.1 gram days of exposure., 7 pages, 3 figures; v2 matches the published version

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.

${\mathrm{Ga}}_{2}{\mathrm{O}}_{3}$ 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.

Particle reflection coefficients for scattering of hydrogen and deuterium atoms from amorphous beryllium, carbon and tungsten were obtained, which are of interest for thermonuclear reactor physics. For the case of deuterium scattering from tungsten the data were also calculated for polycrystalline and crystalline target. The calculations were carried out by two methods: by modeling the trajectories of the incident particles and by using the binary collision approximation. Interaction potentials between hydrogen and helium atoms and the selected materials were calculated in the scope of the density function theory using program DMol for choosing wave functions. The dependence of the reflection coefficient RN on the potential well depth was found. The results demonstrate a good agreement with the available experimental values.

Centre de Calcul Intensif d’Aix-Marseille is acknowledged for granting access to high performance computing ressources.; International audience; Molecular dynamics simulations are used to investigate the behaviour of D atoms at two interfaces between Beryllium (Be) and Beryllium oxide (BeO). After relaxation of the simulation cell, there are (i) localised defects at the interface and (ii) a hexagonal misfit dislocation network creating a succession of compressed and expanded area from each side of the interface. The simulations between 750 K and 1500 K for tens to hundreds of nanoseconds show that both interfaces act as trapping sites for D atoms. The simulations also show that D atoms tend to migrate in the material where the hydrogen isotope solubility is the highest as predicted by thermodynamics. However, the simulations also shows that there are additional kinetic barriers (D trapping sites, D 2 formation/dissociation in BeO) that slow down the path to equilibrium. These additional kinetic barriers may influence the fuel retention and permeation in Be materials.

International audience; ITER will use beryllium as a plasma-facing material in the main chamber, covering a total surface area of about 620 m. Given the importance of beryllium erosion and co-deposition for tritium retention in ITER, significant efforts have been made to understand the behaviour of beryllium under fusion-relevant conditions with high particle and heat loads. This paper provides a comprehensive report on the state of knowledge of beryllium behaviour under fusion-relevant conditions: the erosion mechanisms and their consequences, beryllium migration in JET, fuel retention and dust generation. The paper reviews basic laboratory studies, advanced computer simulations and experience from laboratory plasma experiments in linear simulators of plasma–wall interactions and in controlled fusion devices using beryllium plasma-facing components. A critical assessment of analytical methods and simulation codes used in beryllium studies is given. The overall objective is to review the existing set of data with a broad literature survey and to identify gaps and research needs to broaden the database for ITER.

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.

n this article, we review the molecular dynamics (MD) methods for use in simulations of radiation effects across a broad energy range. We examine the physical limitations of the classical MD for simulation of radiation effects, and present the modifications required to improve MD’s description of high-kinetic energy events. In the high-energy regime, which is known as swift heavy ions, we overview the existing models of extending the classical molecular dynamic methods to include effects of electronic excitations. At the end, we also discuss the complications associated with modelling complex radiation effects and challenges, which remain to be resolved

We investigate the diurnal modulation of the event rate for dark matter scattering on solid targets arising from the directionally dependent defect creation threshold energy. In particular, we quantify how this effect would help in separating dark matter signal from the neutrino background. We perform a benchmark analysis for a germanium detector and compute how the reach of the experiment is affected by including the timing information of the scattering events. We observe that for light dark matter just above the detection threshold the magnitude of the annual modulation is enhanced. In this mass range using either the annual or diurnal modulation information provides a similar gain in the reach of the experiment, while the additional reach from using both effects remains modest. Furthermore, we demonstrate that if the background contains a feature exhibiting an annual modulation similar to the one observed by DAMA experiment, the diurnal modulation provides for an additional handle to separate dark matter signal from the background., Comment: 10 pages, 9 figures

Hydrogen isotopes are retained in materials for fusion power applications, changing both hydrogen embrittlement and tritium inventory as the microstructure undergoes irradiation damage. But modelling of highly damaged materials - exposed to over 0.1 displacements per atom (dpa) - where asymptotic saturation is observed, for example tungsten facing the plasma in a fusion tokamak reactor, is difficult because a highly damaged microstructure cannot be treated as weakly interacting isolated defect traps. In this paper we develop computational techniques to find the defect content in highly irradiated materials without adjustable parameters. First we show how to generate converged high dose (>1 dpa) microstructures using a combination of the creation-relaxation algorithm and molecular dynamics simulations of collision cascades. Then we make robust estimates of point defects and void regions with simple developments of the Wigner-Seitz decomposition of lattice sites. We use our estimates of the void surface area to predict the deuterium retention capacity of tungsten as a function of dose. This is then compared to 3He nuclear reaction analysis (NRA) measurements of tungsten samples self-irradiated at 290 K to different damage doses and exposed to deuterium plasma at low energy at 370 K. We show that our simulated microstructures give an excellent match to the experimental data, with both model and experiment showing 1.5-2.0 at.% deuterium retained in tungsten in the limit of high dose., preprint for submission to journal

This book collects the lectures presented in the first COST TUMIEE Training School held in Greece in 2019, supplemented with specific applications that illustrate how the multi-scale approach is implemented in specific cases of interest. The book is intended both as a reference in the field and as a textbook for people becoming interested or entering the field. The first part focuses on experimental methods, the second on theoretical approaches, and the third on cases of interest.

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

Erosion of material by energetic ions, i.e., sputtering, is widely used in industry and research. Using experiments and simulations that, independently of each other, obtain the sputter yield of thousands of individual grains, we demonstrate here that the sputter yield for heavy keV ions on metals changes as a continuous function of the crystal direction. Moreover, we show that polycrystalline metals with randomly oriented grains do not sputter with the same yield as the amorphous material. The key reason for this is attributed to linear collision sequences rather than channeling.

Intricate topographical patterns can form on the surface of crystalline Ge(001) subject to low-energy ion irradiation in the reverse epitaxy regime, i.e., at elevated temperatures which enable dynamic recrystallization. We compare such nanoscale patterns produced by irradiation from varied polar and azimuthal ion incidence angles with corresponding calculated surface topographies. To this end, we propose a continuum equation including both anisotropic erosive and anisotropic diffusive effects. Molecular dynamics simulations provide the coefficients of angle-dependent sputter erosion for the calculations. By merely changing these coefficients accordingly, the experimentally observed surface morphologies can be reproduced, except for extreme ion incidence angles. Angle-dependent sputter erosion is thereby identified as a dominant mechanism in ion-induced pattern formation on crystalline surfaces under irradiation from off-normal incidence angles.