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Abstract Ga2O3 is a wide-band gap 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. We develop two types of machine-learning Gaussian approximation potentials (ML-GAPs) for Ga2O3 with high accuracy for β/κ/α/δ/γ polymorphs and generality for disordered stoichiometric structures. We release two versions of interatomic potentials in parallel, namely soapGAP and tabGAP, for high accuracy and exceeding speedup, respectively. Both potentials 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. Moreover, the Ga2O3 liquid-solid phase transition proceeds in three different stages. This experimentally unrevealed complex dynamics can be understood in terms of distinctly different mobilities of O and Ga sublattices in the interfacial layer.

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

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

Understanding the underlying physics of vacuum electrical breakdown is of relevance for the development of technologies where breakdown is of significance, either as an intended part of device operation or as a cause of failure. One prominent contemporary case of the latter is high-gradient linear accelerators, where structures must be able to operate with both high surface electric fields and low breakdown rates. Temporal clustering of breakdowns has for long been observed in accelerating structures. In this work, the statistics of breakdown clustering were studied using data collected by a system applying DC voltage pulses over parallel disk electrodes in a vacuum chamber. It was found that the obtained distributions of cluster sizes can be explained by postulating that every breakdown induces a number of follow-up breakdowns that are Poisson-distributed with λ < 1. It was also found that the primary breakdown rate, i.e., the breakdown rate after discounting follow-up breakdowns, fluctuates over time but has no discernible correlation with cluster size. Considered together, these results provide empirical support for the interpretation that primary and follow-up breakdowns are categorically different kinds of events with different underlying causes and mechanisms. Furthermore, they support the interpretation that there is an actual causal relationship between the breakdowns in a cluster rather than them simply being concurrent events with a common underlying cause.

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.

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.

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.

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

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

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.

Breakdowns (BDs) may occur in high-voltage applications even in ultrahigh vacuum conditions. Previously, we showed that it is important to pay attention to the post-BD voltage recovery in order to limit the appearance of secondary BDs associated with the primary ones. This can improve the overall efficiency of the high-voltage device. In this study, we focus on the optimization of the linear post-BD voltage recovery, with the principle aim of alleviating the problem of the secondary BDs. We investigate voltage recovery scenarios with different starting voltages and slopes of linear voltage increase by using a pulsed dc system. We find that a higher number of pulses during the voltage recovery produces fewer secondary BDs and a lower overall BD rate. Lowering the number of pulses led to more dramatic voltage recovery resulting in higher BD rates. A steeper voltage increase rate led to a more localized occurrence of the secondary BDs near the end of the voltage recovery period. It was also found that the peak BD probability is regularly observed around 1 s after the end of the ramping period and that its value decreases exponentially with the amount of energy put into the system during the ramping. The value also decays exponentially with a half-life of (1.4±0.3) ms if the voltage only increased between the voltage recovery steps.

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

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

Vacuum electrical breakdowns, also known as vacuum arcs, are a limiting factor in many devices that are based on application of high electric fields near their component surfaces. Understanding processes that lead to breakdown events may help mitigate their appearance and suggest ways for improving operational efficiency of power-consuming devices. Stability of surface performance at a given value of the electric field is affected by the conditioning state, i.e., how long the surface was exposed to this field. Hence, optimization of the surface conditioning procedure can significantly speed up the preparatory steps for high-voltage applications. In this article, we use pulsed dc systems to optimize the surface conditioning procedure of copper electrodes, focusing on the effects of voltage recovery after breakdowns and variable repetition rates as well as long waiting times between pulsing runs. Despite the differences in the experimental scales, ranging from 10^{-4} s between pulses up to pulsing breaks of 10^{5} s, the experiments show that the longer the idle time between the pulses, the more probable it is that the next pulse produces a breakdown. We also notice that secondary breakdowns, i.e., those which correlate with the previous ones, take place mainly during the voltage recovery stage. We link these events with deposition of residual atoms from vacuum on the electrode surfaces. Minimizing the number of pauses during the voltage recovery stage reduces power losses due to secondary breakdown events, improving efficiency of the surface conditioning.

Conditioning of a metal structure in a high-voltage system is the progressive development of resistance to vacuum arcing over the operational life of the system. This is, for instance, seen during the initial operation of radio frequency (rf) cavities in particle accelerators. It is a relevant topic for any technology where breakdown limits performance and where conditioning continues for a significant duration of system run time. Projected future linear accelerators require structures with accelerating gradients of up to 100 MV/m. Currently, this performance level is achievable only after a multimonth conditioning period. In this work, a pulsed dc system applying voltage pulses over parallel disk electrodes was used to study the conditioning process, with the objective of obtaining insight into its underlying mechanics and, ultimately, to find ways to shorten the conditioning process. Two kinds of copper electrodes were tested: as-prepared machine-turned electrodes (“hard” copper) and electrodes that additionally had been subjected to high-temperature treatments (“soft” copper). The conditioning behavior of the soft electrodes was found to be similar to that of comparably treated accelerating structures, indicating a similar conditioning process. The hard electrodes reached the same ultimate performance as the soft electrodes much faster, with a difference of more than an order of magnitude in the number of applied voltage pulses. Two distinctly different distributions of breakdown locations were observed on the two types of electrodes. Considered together, our results support the crystal structure dislocation theory of breakdown and suggest that the conditioning of copper in high field systems such as rf accelerating structures is dominated by material hardening.

Understanding the microscopic phenomena behind vacuum arc ignition and generation is crucial for being able to control the breakdown rate, thus improving the effectiveness of many high-voltage applications where frequent breakdowns limit the operation. In this work, statistical properties of various aspects of breakdown, such as the number of pulses between breakdowns, breakdown locations and crater sizes are studied independently with almost identical pulsed dc systems at the University of Helsinki and in CERN. In high-gradient experiments, copper electrodes with parallel plate capacitor geometry, undergo thousands of breakdowns. The results support the classification of the events into primary and secondary breakdowns, based on the distance and number of pulses between two breakdowns. Primary events follow a power law on the log–log scale with the slope α≈1.30, while the secondaries are highly dependent on the pulsing parameters.

Irradiation of a sharp tungsten tip by a femtosecond laser and exposed to a strong DC electric field led to reproducible surface modifications. By a combination of field emission microscopy and scanning electron microscopy, we observed asymmetric surface faceting with sub-ten nanometer high steps. The presence of faceted features mainly on the laser-exposed side implies that the surface modification was driven by a laser-induced transient temperature rise on a scale of a couple of picoseconds in the tungsten tip apex. Moreover, we identified the formation of a nano-tip a few nanometers high located at one of the corners of a faceted plateau. The results of simulations emulating the experimental conditions are consistent with the experimental observations. The presented technique would be a new method to fabricate a nano-tip especially for generating coherent electron pulses. The features may also help to explain the origin of enhanced field emission, which leads to vacuum arcs, in high electric field devices such as radio-frequency particle accelerators.

Ion beam processing of surfaces is well known to lead to sputtering, which conventionally is associated only with erosion of atoms from the material. We show here, by combination of experiments and a newly developed Monte Carlo algorithm, that in the case of nanoparticles in a regular two-dimensional array on surfaces, the redeposition of sputtered atoms may play a significant role on the system development. The simulations are directly compared to in situ experiments obtained using a dual focused Ga ^+ ion beam system and high resolution scanning electron microscopy, and explain the size evolution by a combination of sputtering and redeposition of sputtered material on neighboring particles. The effect is found to be dependent on the size of the nanoparticles: if the nanoparticle size is comparable to the ion range, the reposition is negligible. For larger nanoparticles the redeposition becomes significant and is able to compensate up to 20% of the sputtered material, effectively reducing the process of sputtering. The redeposition may even lead to significant growth: this was seen for the nanoparticles with the sizes much smaller than the ion range. Furthermore, the algorithm shows that significant redeposition is possible when the large size neighboring nanoparticles are present.

In an increasing number of high-gradient linear accelerator applications, accelerating structures must operate with both high surface electric fields and low breakdown rates. Understanding the statistical properties of breakdown occurrence in such a regime is of practical importance for optimizing accelerator conditioning and operation algorithms, as well as of interest for efforts to understand the physical processes which underlie the breakdown phenomenon. Experimental data of breakdown has been collected in two distinct high-gradient experimental set-ups: A prototype linear accelerating structure operated in the Compact Linear Collider Xbox 12 GHz test stands, and a parallel plate electrode system operated with pulsed DC in the kV range. Collected data is presented, analyzed and compared. The two systems show similar, distinctive, two-part distributions of number of pulses between breakdowns, with each part corresponding to a specific, constant event rate. The correlation between distance and number of pulses between breakdown indicates that the two parts of the distribution, and their corresponding event rates, represent independent primary and induced follow-up breakdowns. The similarity of results from pulsed DC to 12 GHz rf indicates a similar vacuum arc triggering mechanism over the range of conditions covered by the experiments.