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Ville Jansson

Publications and source records attributed to Ville Jansson.

16 recordsLinked to original sources

Polarization characteristics of adatoms self-diffusing on metal surfaces under high electric fields

Although atomic diffusion on metal surfaces under high electric fields has been studied theoretically and experimentally since the 1970s, its accurate and quantitative theoretical description remains a significant challenge. In our previous work, we developed a theoretical framework that describes the atomic dynamics on metal surfaces in the presence of an electric field in terms of the local polarization characteristics of the surface at the vicinity of a moving atom. Here, we give a deeper analysis of the physics underlying this framework, introducing and rigorously defining the concept of the effective polarization characteristics (permanent dipole moment $μ$ and polarizability $α$) of a moving atom on a metal surface, which are shown to be the relevant atomic quantities determining the dynamics of a moving atom via a compact equation. We use density functional theory (DFT) to calculate $μ$ and $α$ of a W adatom moving on a W {110} surface, where additional adatoms are present in its vicinity. We analyze the dependence of $μ$ and $α$ and hence the migration barriers under electric fields on the local atomic environments (LAE) of an adatom. We find that the LAE significantly affects $μ$ and $α$ of a moving atom in the limited cases we studied, which implies that further systematic DFT calculations are needed to fully parameterize surface diffusion in terms of energy barriers for long-term large scale simulations, such as our recently developed Kinetic Monte Carlo model for surface diffusion under electric field.

cond-mat.mtrl-sci

Growth mechanism for nanotips in high electric fields

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

cond-mat.mtrl-sci

Data sets and trained neural networks for Cu migration barriers

Kinetic Monte Carlo (KMC) is an efficient method for studying diffusion. A limiting factor to the accuracy of KMC is the number of different migration events allowed in the simulation. Each event requires its own migration energy barrier. The calculation of these barriers may be unfeasibly expensive. In this article we present a data set of migration barriers on for nearest-neighbour jumps on the Cu surfaces, calculated with the nudged elastic band (NEB) method and the tethering force approach. We used the data to train artifcial 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.

physics.comp-ph

Application of artificial neural networks for rigid lattice kinetic Monte Carlo studies of Cu surface diffusion

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.

physics.comp-ph

Tungsten migration energy barriers for surface diffusion: a parameterization for KMC simulations

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.

cond-mat.mtrl-sci

Atomistic behavior of metal surfaces under high electric fields

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.

cond-mat.mtrl-sci

Au nanowire junction breakup through surface atom diffusion

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

cond-mat.mtrl-sci

Migration barriers for surface diffusion on a rigid lattice: challenges and solutions

Atomistic rigid lattice Kinetic Monte Carlo is an efficient method for simulating nano-objects and surfaces at timescales much longer than those accessible by molecular dynamics. A laborious part of constructing any Kinetic Monte Carlo 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. One of the common methods of barrier calculations is Nudged Elastic Band. The number of barriers needed to fully describe simulated systems is typically between hundreds of thousands and millions. Calculations of such a large number of barriers of various processes is far from trivial. In this paper, we will discuss the challenges arising during barriers calculations on a surface and present a systematic and reliable tethering force approach to construct a rigid lattice barrier parameterization of face-centred and body-centred cubic metal lattices. We have produced several different barrier sets for Cu and for Fe that can be used for KMC simulations of processes on arbitrarily rough surfaces. The sets are published as Data in Brief articles and available for the use.

cond-mat.mtrl-sci

Cu self-sputtering MD simulations for 0.1-5 keV ions at elevated temperatures

Self-sputtering of copper under high electric fields is considered to contribute to plasma buildup during a vacuum breakdown event frequently observed near metal surfaces, even in ultra high vacuum condition in different electric devices. In this study, by means of molecular dynamics simulations, we analyze the effect of surface temperature and morphology on the yield of self-sputtering of copper with ion energies of 0.1-5 keV. We analyze all three low-index surfaces of Cu, {100}, {110} and {111}, held at different temperatures, 300 K, 500 K and 1200 K. The surface roughness relief is studied by either varying the angle of incidence on flat surfaces, or by using arbitrary roughened surfaces, which result in a more natural distribution of surface relief variations. Our simulations provide detailed characterization of copper self-sputtering with respect to different material temperatures, crystallographic orientations, surface roughness, energies, and angles of ion incidence.

cond-mat.mtrl-sci

Adatom diffusion in high electric fields

Strong electric fields are known to create biased adatom migration on metallic surfaces. We present a Kinetic Monte Carlo model that can simulate adatom migration on a tungsten (W) surface in electric fields. We validate our model by using it to calculate the drift velocity of the adatom at different fields and temperature and comparing the results with experimental data from the literature. We obtain excellent agreement.

cond-mat.mtrl-sci

Simulations of surface stress effects in nanoscale single crystals

Onset of vacuum arcing near a metal surface is often associated with nanoscale asperities, which may dynamically appear due to different processes ongoing in the surface and subsurface layers in the presence of high electric fields. Thermally activated processes, as well as plastic deformation caused by tensile stress due to an applied electric field, are usually not accessible by atomistic simulations because of long time needed for these processes to occur. On the other hand, finite element methods, able to describe the process of plastic deformations in materials at realistic stresses, do not include surface properties. The latter are particularly important for the problems where the surface plays crucial role in the studied process, as for instance, in case of plastic deformations at a nanovoid. In the current study by means of molecular dynamics and finite element simulations we analyse the stress distribution in single crystal copper containing a nanovoid buried deep under the surface. We have developed a methodology to incorporate the surface effects into the solid mechanics framework by utilizing elastic properties of crystals, pre-calculated using molecular dynamic simulations. The method leads to computationally efficient stress calculations and can be easily implemented in commercially available finite element software, making it an attractive analysis tool.

cond-mat.mtrl-sci

Long-term stability of Cu surface nanotips

Sharp nanoscale tips on metal surfaces of electrodes enhance locally applied electric fields. Strongly enhanced electric fields trigger electron field emission and atom evaporation from the apexes of the nanotips. Combined together, these processes may explain electric discharges in form of small local arcs observed near metal surfaces in the presence of electric fields even in ultra high vacuum conditions. In the present work we investigate the stability of nanoscale tips by means of computer simulations of surface diffusion processes on copper (Cu), the main material of high voltage electronics. We study the stability and life-time of thin Cu surface nanotips at different temperatures in terms of diffusion processes. For this purpose, we have developed a surface Kinetic Monte Carlo (KMC) model where the jump processes are described by tabulated precalculated energy barriers. We show that tall surface features with high aspect ratios can be fairly stable at room temperature. However, the stability was found to depend strongly on the temperature: 13 nm nanotips with the major axes in the <110> crystallographic directions were found to flatten down to half of the original height in less than 100 ns at temperatures close to the melting point, whereas no significant change in the height of these nanotips was observed after 10 $μ$s at room temperature. Moreover, the nanotips built up along the <110> crystallographic directions were found significantly more stable than those oriented in the <100> or <111> crystallographic directions. The proposed KMC model has been found well suited for simulating atomic surfaces processes and was validated against Molecular Dynamics (MD) simulation results via the comparison of the flattening times obtained by both methods. We also note that the KMC simulations were two orders of magnitude computationally faster than the corresponding MD calculations.

cond-mat.mtrl-sci

Sink strength calculations of dislocations and loops using OKMC

We calculate the sink strength of dislocations and toroidal absorbers using Object Kinetic Monte Carlo and compare with the theoretical expressions. We get good agreement for dislocations and loop-shaped absorbers of 3D migrating defects, provided that the volume fraction is low, and fair agreements for dislocations with 1D migrating defects. The master curve for the 3D to 1D transition is well reproduced with loop-shaped absorbers and fairly well with dislocations. We conclude that, on the one hand, the master curve is correct for a wide range of sinks and that, on the other, OKMC techniques inherently take correctly into account the strengths of sinks of any shape, provided that an effective way of appropriately inserting the sinks to be studied can be found.

cond-mat.mtrl-sci

The nanostructure evolution in Fe-C systems under irradiation at 560 K

This work extends our Object Kinetic Monte Carlo model for neutron irradiation-induced nanostructure evolution in Fe-C alloys to consider higher irradiation temperatures. The previous study concentrated on irradiation temperatures < 370 K. Here we study the evolution of vacancy and self-interstitial atom (SIA) cluster populations at the operational temperature of light water reactors, by simulating specific reference irradiation experiments. Following our previous study, the effect of carbon on radiation defect evolution can be described in terms of formation of immobile complexes with vacancies, that in turn act as traps for SIA clusters. This dynamics is simulated using generic traps for SIA and vacancy clusters. The traps have a binding energy that depends on the size and type of the clusters and is also chosen on the basis of previously performed atomistic studies. The model had to be adapted to account for the existence of two kinds of SIA clusters, <111> and <100>, as observed in electron microscopy examinations of Fe alloys neutron irradiated at the temperatures of technological interest. The model, which is fully based on physical considerations and only uses a few parameters for calibration, is found to be capable of reproducing the experimental trends, thereby providing insight into the physical mechanisms of importance to determine the type of nanostructural evolution undergone by the material during irradiation.

cond-mat.mtrl-sci

OKMC simulations of Fe-C systems under irradiation: sensitivity studies

This paper continues our previous work on a nanostructural evolution model for Fe-C alloys under irradiation, using Object Kinetic Monte Carlo modeling techniques. We here present a number of sensitivity studies of parameters of the model, such as the carbon content in the material, represented by generic traps for point defects, the importance of traps, the size dependence of traps and the effect of the dose rate.

cond-mat.mtrl-sci

Simulation of the nanostructure evolution under irradiation in Fe-C alloys

Neutron irradiation induces in steels nanostructural changes, which are at the origin of the mechanical degradation that these materials experience during operation in nuclear power plants. Some of these effects can be studied by using as model alloy the iron-carbon system. The Object Kinetic Monte Carlo technique has proven capable of simulating in a realistic and quantitatively reliable way a whole irradiation process. We have developed a model for simulating Fe-C systems using a physical description of the properties of vacancy and self-interstitial atom (SIA) clusters, based on a selection of the latest data from atomistic studies and other available experimental and theoretical work from the literature. Based on these data, the effect of carbon on radiation defect evolution has been largely understood in terms of formation of immobile complexes with vacancies that in turn act as traps for SIA clusters. It is found that this effect can be introduced using generic traps for SIA and vacancy clusters, with a binding energy that depends on the size of the clusters, also chosen on the basis on previously performed atomistic studies. The model proved suitable to reproduce the results of low (<350 K) temperature neutron irradiation experiments, as well as the corresponding post-irradiation annealing up to 700 K, in terms of defect cluster densities and size distribution, when compared to available experimental data from the literature. The use of traps proved instrumental for our model.

cond-mat.mtrl-sci