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[en] Molecular dynamics (MD) simulations are used to investigate the response of a/2<111> screw dislocation in iron submitted to pure shear strain. The dislocation glides and remains in a (110) plane; the motion occurs exclusively through the nucleation and propagation of double kinks. The critical stress is calculated as a function of the temperature. A new method is developed and used to determine the activation energy of the double kink mechanism from MD simulations. It is shown that the differences between experimental and simulation conditions lead to a significant difference in activation energy. These differences are explained, and the method developed provides the link between MD and mesoscopic simulations

[en] The REVE (Reactor for Virtual Experiments) project is an international joint effort aimed at developing multi-scale modelling computational toolboxes capable of simulating the behaviour of materials under irradiation at different time and length scales. Well grounded numerical techniques such as molecular dynamics (MD) and Monte Carlo (MC) algorithms, as well as rate equation (RE) and dislocation-defect interaction theory, form the basis on which the project is built. The goal is to put together a suite of integrated codes capable of deducing the changes in macroscopic properties starting from a detailed simulation of the microstructural changes produced by irradiation in materials. To achieve this objective, several European laboratories are closely collaborating, while exchanging data with American and Japanese laboratories currently pursuing similar approaches. The material chosen for the first phase of this project is reactor pressure vessel (RPV) steel, the target macroscopic magnitude to be predicted being the yield strength increase (Δσy) due, essentially, to irradiation-enhanced formation of intragranular solute atom precipitates or clouds, as well as irradiation induced defects in the matrix, such as point defect clusters and dislocation loops. A description of the methodological approach used in the project and its current state is given in the paper. The development of the simulation tools requires a continuous feedback from ad hoc experimental data. In the framework of the REVE project SCK EN has therefore performed a neutron irradiation campaign of model alloys of growing complexity (from pure Fe to binary and ternary systems and a real RPV steel) in the Belgian test reactor BR2 and is currently carrying on the subsequent materials characterisation using its hot cell facilities. The paper gives the details of this experimental programme - probably the first large-scale one devoted to the validation of numerical simulation tools - and presents and discusses the first available results, with a view to their use as feedback for the improvement of the computational modelling. (authors)

[en] The sink strength for three-dimensionally (3D) versus one-dimensionally (1D), or mixed 1D/3D, migrating defects in irradiated materials has attracted much attention in the recent past, because many experimental observations cannot be interpreted unless 1D or mixed 1D/3D migration patterns are assumed for self-interstitial atom clusters produced in cascades during irradiation. Analytical expressions for the sink strengths for defects migrating in 3D and also in 1D have been therefore developed and a 'master curve' approach has been proposed to describe the transition from purely 1D to purely 3D defect migration. Object kinetic Monte Carlo (OKMC) methods have subsequently been used to corroborate the theoretical expressions but, although good agreement was generally found, the ability of this technique to reach the 1D migration limit has been questioned, the limited size of the simulation box used in OKMC studies having been mainly blamed for the inadequacies of the model. In the present work, we explore the capability of OKMC to reproduce the sink strengths of spherical absorbers in a wide range of volume fractions, together with the sink strength of grain boundaries, for defects characterised by different migration dimensionality, from fully 3D to pure 1D. We show that this technique is not only capable of reproducing the theoretical expressions for the sink strengths in the whole range of conditions explored, but is also sensitive enough to reveal the necessity of correcting the theoretical expressions for large sink volume fractions. We thereby demonstrate that, in spite of the limited size of the OKMC simulation box, the method is suitable to describe the microstructure evolution of irradiated materials for any defect migration pattern, including fully 1D migrating defects, as well as to allow for the effect of extended microstructural features, much larger than the simulation box, such as grain boundaries

[en] In alloys, the different elements interact with each other as well as with the various defects present: point defects or extended defects (stacking faults, dislocations, grain boundaries). These interactions are responsible for the elementary mechanisms governing the kinetics of the system, and they are among the key parameters to model the time evolution of the microstructure, under ageing or irradiation. Indeed the microstructure properties are directly linked to the chemical interactions between the different constituting elements, and these defects. Ab initio methods allow to determine properties such as defect formation, binding or migration energies. These crucial quantities can shed light on the various mechanisms involved in the evolution of the microstructure as well as be used as input for various models. In this article, data obtained by ab initio calculation of point defects (vacancies and self-interstitial atoms, foreign interstitial defects (C, N, H and He) in different matrix element (Fe and Zr) as well as of some substitutional elements (Cu, Ni, Mn, Si, Cr and P ...)) in bcc Fe will be presented and discussed. When available, comparison with experimental data will be made in order to assess the validity of the results. The link between the obtained atomic quantities and the related consequences on the macroscopic properties will be discussed

[en] The effect of He impurities on the properties and behavior of self-interstitial atom (SIA) clusters in α-Fe has been simulated by atomistic molecular dynamics (MD) and molecular statics (MS) simulation techniques using semi-empirical interatomic potentials and compared to ab initio electronic structure calculations. The MD simulations reveal many interactions between He and SIA clusters, including a spontaneous SIA-substitutional He recombination and replacement mechanism that ejects He into interstitial positions and a strong interaction between He, in either interstitial or substitutional positions, with SIA and SIA clusters and also with other He atoms. The MS calculations reveal relatively small interaction trapping radii of about 1 nm between interstitial He and SIA cluster complexes, but strong binding energies from 1.3 to 4.4 eV, depending on cluster size and interaction geometry. The comparisons between the ab initio and semi-empirical interactions are in generally good agreement and indicate that the He-point defect interactions in bcc Fe are well represented by considering the displacement (strain) field interactions amongst the defects

[en] The collective behavior of dislocations in reactor pressure vessel (RPV) steel involves dislocation properties on different phenomenological scales. In the multiscale approach, adopted in this work, we use atomic simulations to provide input data for larger scale simulations. We show in this paper how first-principles calculations can be used to describe the Peierls potential of screw dislocations, allowing for the validation of the empirical interatomic potential used in molecular dynamics simulations. The latter are used to compute the velocity of dislocations as a function of the applied stress and the temperature. The mobility laws obtained in this way are employed in dislocation dynamics simulations in order to predict properties of plastic flow, namely dislocation-dislocation interactions and dislocation interactions with carbides at low and high temperature.

[en] We have developed a two-band model of Fe-Cr, fitted to properties of the ferromagnetic alloy. Fitting many-body functionals to the calculated mixing enthalpy of the alloy and the mixed interstitial binding energy in iron, our potential reproduces changes in sign of the formation energy as a function of Cr concentration. When applied in kinetic Monte Carlo simulations, the potential correctly predicts decomposition of initially random Fe-Cr alloys into the α-prime phase as function of Cr concentration

[en] The quality of kinetic Monte Carlo (KMC) simulations of microstructure evolution in alloys relies on the parametrization of point-defect migration rates, which are complex functions of the local chemical composition and can be calculated accurately with ab initio methods. However, constructing reliable models that ensure the best possible transfer of physical information from ab initio to KMC is a challenging task. This work presents an innovative approach, where the transition rates are predicted by artificial neural networks trained on a database of 2000 migration barriers, obtained with density functional theory (DFT) in place of interatomic potentials. The method is tested on copper precipitation in thermally aged iron alloys, by means of a hybrid atomistic-object KMC model. For the object part of the model, the stability and mobility properties of copper-vacancy clusters are analyzed by means of independent atomistic KMC simulations, driven by the same neural networks. The cluster diffusion coefficients and mean free paths are found to increase with size, confirming the dominant role of coarsening of medium- and large-sized clusters in the precipitation kinetics. The evolution under thermal aging is in better agreement with experiments with respect to a previous interatomic-potential model, especially concerning the experiment time scales. However, the model underestimates the solubility of copper in iron due to the excessively high solution energy predicted by the chosen DFT method. Nevertheless, this work proves the capability of neural networks to transfer complex ab initio physical properties to higher-scale models, and facilitates the extension to systems with increasing chemical complexity, setting the ground for reliable microstructure evolution simulations in a wide range of alloys and applications. (authors)

[en] Duplex stainless steel loses impact toughness quickly during its service at nuclear power plant station as pipe and boiler. Aging induced spinodal decomposition in ferrite phase is the mechanism behind this degradation. This work uses electropulsing to treat the aged steel at the service temperature. The charpy impact toughness and Vickers micro-hardness were recovered significantly. Thermoelectric power is recommended to measure the degree of spinodal decomposition in the aging processing, which was recovered by > 83% by the electropulsing treatment. It was proved that the anti-aging treatment was not due to the Ohm heating. Instead, the electropulsing-induced extra free energy change of − 891 J/mol provided thermodynamic driving force for the regeneration processing. Electropulsing-enhanced diffusivity enables the anti-aging processing to be completed quickly.