Simon Vigonski

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

Abstract 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.

Molecular dynamics simulations of near-surface Fe precipitates in Cu under high electric fields

High electric fields in particle accelerators cause vacuum breakdowns in the accelerating structures. The breakdowns are thought to be initiated by the modification of material surface geometry under high electric fields. These modifications in the shape of surface protrusions enhance the electric field locally due to the increased surface curvature. Using molecular dynamics, we simulate the behaviour of Cu containing a near-surface Fe precipitate under a high electric field. We find that the presence of a precipitate under the surface can cause the nucleation of dislocations in the material, leading to the appearance of atomic steps on the surface. Steps resulting from several precipitates in close proximity can also form protruding plateaus. Under very high external fields, in some cases, we observed the formation of voids above or below the precipitate, providing additional dislocation nucleation sites.

Application of multiphysics and multiscale simulations to optimize industrial wood drying kilns

Timber industry and export are an important part of Estonian economy, making affordable industrial scale equipment an important investment for small or starting companies. These companies often develop on-site equipment for wood processing and drying, utilizing pre-existing infrastructure to minimize cost and risk. However, under these conditions custom design of the wood drying kilns is often required.In the present study, a finite element simulation based approach is used to simulate and optimize the industrial wood drying process and the design of the custom-made kilns in a multiscale-multiphysics modeling framework. Air flow is calculated by the Navier-Stokes equations or ?-e turbulence model followed by heat transport in the solid and gas phase and moisture dynamics in wood and air. The dense packing of the processed materials is handled by utilizing a porous media approach and homogenization procedure, leading to effective simulations of the moisture and heat balance.Multiphysics-multiscale simulations are successfully adapted to optimize the industrial design of wood drying kilns. The optimization of the kiln design is achieved by estimating the necessary ventilating power and ensuring homogeneous drying of the processed material.

Au nanowire junction breakup through surface atom diffusion

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

Verification of a multiscale surface stress model near voids in copper under the load induced by external high electric field

In the current study we use a model of surface stress for finite element method calculations to complement existing bulk stress models. The resulting combined model improves the accuracy of stress calculations near nanoscale imperfections in the material. We verify the results by simulating differently-shaped voids in single crystal copper both with FEM and with molecular dynamics, and compare the resulting stress distributions. The compared results agree well within small uncertainties, indicating that the implemented surface stress model is able to capture all the major features of the stress distributions in the material. Discrepancies occur near surfaces, where the crystal faces were not defined explicitly in the model. The fast and accurate FEM calculations can be used to estimate the stress concentration of specific extended defects, such as voids, while studying the dislocation-mediated mechanisms near these defects in the presence of external stresses by atomistic techniques.

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

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

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

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