Abrupt elastic-to-plastic transition in pentagonal nanowires under bending

MD modeling and calculations were supported by Russian Science Foundation project grant 18-19-00645 “Adhesion of polymer-based soft materials: from liquid to solid”; mechanical testing and FEM simulations were supported by Estonian Research Council projects PUT1689 and PUT1372.In this study, pentagonal Ag and Au nanowires (NWs) were bent in cantilever beam configuration inside a scanning electron microscope. We demonstrated an unusual, abrupt elastic-to-plastic transition, observed as a sudden change of the NW profile from smooth arc-shaped to angled knee-like during the bending in the narrow range of bending angles. In contrast to the behavior of NWs in the tensile and three-point bending tests, where extensive elastic deformation was followed by brittle fracture, in our case, after the abrupt plastic event, the NW was still far from fracture and enabled further bending without breaking. A possible explanation is that the five-fold twinned structure prevents propagation of critical defects, leading to dislocation pile up that may lead to sudden stress release, which is observed as an abrupt plastic event. Moreover, we found that if the NWs are coated with alumina, the abrupt plastic event is not observed and the NWs can withstand severe deformation in the elastic regime without fracture. The coating may possibly prevent formation of dislocations. Mechanical durability under high and inhomogeneous strain fields is an important aspect of exploiting Ag and Au NWs in applications like waveguiding or conductive networks in flexible polymer composite materials.Eesti Teadusagentuur PUT1372,PUT1689; Russian Science Foundation 18-19-00645; Institute of Solid State Physics, University of Latvia as the Center of Excellence has received funding from the European Union’s Horizon 2020 Framework Programme H2020-WIDESPREAD-01-2016-2017-TeamingPhase2 under grant agreement No. 739508, project CAMART

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.Peer reviewe

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.Peer reviewe

The effect of heat treatment on the morphology and mobility of Au nanoparticles

This work was supported by The Centre National de la Recherche Scientifique (CNRS) of France and the French Embassy Program. The authors are also grateful for partial support by COST Action CA15216, the Estonian Science Foundation (grants PUT1689 and PUT1372), the Estonian Centre of Excellence in Zero Energy and Resource Efficient Smart Buildings and Districts, ZEBE, grant 2014-2020.4.01.15.0016 and Latvian Science Council grant lzp-2018/2-0083.In the present paper, we investigate the effect of heat treatment on the geometry and mobility of Au nanoparticles (NPs) on a Si substrate. Chemically synthesized Au NPs of diameter ranging from 5 to 27 nm were annealed at 200, 400, 600 and 800 °C for 1 h. A change in the geometry from faceted to more rounded shapes were observed with increasing annealing temperature. Kinetic Monte Carlo simulations indicate that the NPs become rounded due to the minimization of the surface area and the transition to lower energy surface types (111) and (100). The NPs were manipulated on a silica substrate with an atomic force microscope (AFM) in tapping mode. Initially, the NPs were immovable by AFM energy dissipation. However, annealed NPs became movable, and less energy was required to displace the NPs annealed at higher temperature. However, after annealing at 800 °C, the particles became immovable again. This effect was attributed to the diffusion of Au into the Si substrate and to the growth of the SiO2 layer.Centre National de la Recherche Scientifique; Latvian Council of Science lzp-2018/2-0083; Eesti Teadusfondi PUT1372,PUT1689,2014-2020.4.01.15.0016; European Cooperation in Science and Technology CA15216; Institute of Solid State Physics, University of Latvia as the Center of Excellence has received funding from the European Union’s Horizon 2020 Framework Programme H2020-WIDESPREAD-01-2016-2017-TeamingPhase2 under grant agreement No. 739508, project CAMART²https://www.beilstein-journals.org/bjnano/content/pdf/2190-4286-11-6.pd

Ab initio calculation of field emission from metal surfaces with atomic-scale defects

In this work we combine density functional theory and quantum transport calculations to study the influence of atomic-scale defects on the work function and field emission characteristics of metal surfaces. We develop a general methodology for the calculation of the field emitted current density from nanofeatured surfaces, which is then used to study specific defects on a Cu(111) surface. Our results show that the inclusion of a defect can significantly locally enhance the field emitted current density. However, this increase is attributed solely to the decrease of the work function due to the defect, with the effective field enhancement being minute. Finally, the Fowler-Nordheim equation is found to be valid when the modified value for the work function is used, with only an approximately constant factor separating the computed currents from those predicted by the Fowler-Nordheim equation.Peer reviewe

Dynamic coupling of a finite element solver to large-scale atomistic simulations

We propose a method for efficiently coupling the finite element method with atomistic simulations, while using molecular dynamics or kinetic Monte Carlo techniques. Our method can dynamically build an optimized unstructured mesh that follows the geometry defined by atomistic data. On this mesh, different multiphysics problems can be solved to obtain distributions of physical quantities of interest, which can be fed back to the atomistic system. The simulation flow is optimized to maximize computational efficiency while maintaining good accuracy. This is achieved by providing the modules for a) optimization of the density of the generated mesh according to requirements of a specific geometry and b) efficient extension of the finite element domain without a need to extend the atomistic one. Our method is organized as an open-source C++ code. In the current implementation, an efficient Laplace equation solver for calculation of electric field distribution near rough atomistic surface demonstrates the capability of the suggested approach.Peer reviewedPeer reviewe