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.

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.

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.

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.

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.

Formation Mechanism of Fe Nanocubes by Magnetron Sputtering Inert Gas Condensation.

In this work, we study the formation mechanisms of iron nanoparticles (Fe NPs) grown by magnetron sputtering inert gas condensation and emphasize the decisive kinetics effects that give rise specifically to cubic morphologies. Our experimental results, as well as computer simulations carried out by two different methods, indicate that the cubic shape of Fe NPs is explained by basic differences in the kinetic growth modes of {100} and {110} surfaces rather than surface formation energetics. Both our experimental and theoretical investigations show that the final shape is defined by the combination of the condensation temperature and the rate of atomic deposition onto the growing nanocluster.