O. Box 43 (Pehr Kalms gata 2), FI-00014 University of Helsinki, Finland h i g h l i g h t sWe can model the accumulation of radiation damage in Fe-C. The effect of carbon is to form C-vacancy complexes that in turn trap SIA clusters. The model was successfully used to simulate irradiation at <370 K and post-irradiation annealing. a b s t r a c tNeutron 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.

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. We, thus, construct a comprehensive deposition rate-temperature diagram of Fe NP shapes and develop an analytical model that predicts the temporal evolution of these properties. Combining the shape diagram and the analytical model, morphological control of Fe NPs during formation is feasible; as such, our method proposes a roadmap for experimentalists to engineer NPs of desired shapes for targeted applications.

Sharp nanoscale tips on the metal surfaces of electrodes enhance locally applied electric fields. Strongly enhanced electric fields trigger electron field emission and atom evaporation from the apexes of nanotips. Together, these processes may explain electric discharges in the 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, the main material used in high-voltage electronics. We study the stability and lifetime of thin copper (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 [Formula: see text] 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 [Formula: see text] at room temperature. Moreover, the nanotips built up along the [Formula: see text] crystallographic directions were found to be significantly more stable than those oriented in the [Formula: see text] or [Formula: see text] crystallographic directions. The proposed KMC model has been found to be well-suited for simulating atomic surface processes and was validated against molecular dynamics 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 molecular dynamics calculations.

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.

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.hardening and embrittlement are understood involves the contribution of three damage components: (i) matrix damage, (ii) precipitates, and (iii) grain boundary de-cohesion due to segregation [1]. It is generally assumed that the first component, dominated by pointdefects created in the matrix (iron), can be studied by reference to the behaviour of Fe-C [2].

a b s t r a c tAtomistic 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.

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