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1. How precisely are solute clusters in RPV steels characterized by atom probe experiments?

Author

Castin, N., Klups, P., Konstantinovic, M., Bonny, G., Pascuet, M. I., Moody, M., and Malerba, L.

Subjects
Condensed Matter - Materials Science
Abstract

Atom probe tomography (APT) is a powerful microscopy technique to characterize nano-sized clusters of the alloying elements in the bulk of reactor pressure vessel (RPV) steels. These clusters are known to dominantly determine the evolution of mechanical properties under irradiation. The results are conventionally summarized as the overall number density N and the average diameter D of the solute clusters identified in the material. Here, we demonstrate that these descriptors are intrinsically imprecise because they are steered by the parameters involved in the measurement and data processing, some of which are directly under the control of the operators, but some others not. Consequently, a direct comparison between data derived at different laboratories is compromised, and key trends such as the evolution with dose, are masked. This study relies on a state-of-the-art physical model for neutron irradiation in steels to make reliable estimates of the true microstructure before the measurement is performed, which allows the prediction of the population of solute clusters that are not seen by APT. We mimic APT measurements from simulated microstructures, performing a detailed study of the effects of the parameters of the analysis. We show that the values of N and D reported in the scientific literature can be matched by the predictions of our theoretical model only if specific sets of parameters are used for each laboratory that issued the measurements. We also show that if, on the contrary, all studied cases are analyzed in a consistent way, the scatter of N and D values is reduced.

Published
2024

2. Multiscale modelling in nuclear ferritic steels: from nano-sized defects to embrittlement

Author

Castin, N., Bonny, G., Konstantinović, M. J., Bakaev, A., Bergner, F., Courilleau, C., Domain, C., Gómez-Ferrer, B., Hyde, J. M., Messina, L., Monnet, G., Pascuet, M. I., Radiguet, B., Serrano, M., and Malerba, L.

Subjects
Condensed Matter - Materials Science, 82-XX
Abstract

Radiation-induced embrittlement of nuclear steels is one of the main limiting factors for safe long-term operation of nuclear power plants. In support of accurate and safe reactor pressure vessel (RPV) lifetime assessments, we developed a physics-based model that predicts RPV steel hardening and subsequent embrittlement as a consequence of the formation of nano-sized clusters of minor alloying elements. This model is shown to provide reliable assessments of embrittlement for a very wide range of materials, with higher accuracy than industrial correlations. The core of our model is a multiscale modelling tool that predicts the kinetics of solute clustering, given the steel chemical composition and its irradiation conditions. It is based on the observation that the formation of solute clusters ensues from atomic transport driven by radiation-induced mechanisms, differently from classical nucleation-and-growth theories. We then show that the predicted information about solute clustering can be translated into a reliable estimate for radiation-induced embrittlement, via standard hardening laws based on the dispersed barrier model. We demonstrate the validity of our approach by applying it to hundreds of nuclear reactors vessels from all over the world., Comment: 22 pages, 9 figures

Published
2022

4. The dominating mechanisms for the formation of solute-rich clusters in steels under irradiation

Author

Castin, N., Bonny, G., Bakaev, A., Bergner, F., Domain, C., Hyde, J. M., Messina, L., Radiguet, B., and Malerba, L.

Subjects
Condensed Matter - Materials Science
Abstract

The formation of nano-sized, coherent, solute-rich clusters (NSRC) is known to be an important factor degrading the macroscopic properties of steels under irradiation. The mechanisms driving their formation are still debated. This work focuses on low-Cu reactor pressure vessel (RPV) steels, where solute species are generally not expected to precipitate. We rationalize the processes taking place at the nanometre scale under irradiation, relying on the latest theoretical and experimental evidence on atomic-level diffusion and transport processes. These are compiled in a new model, based on the object kinetic Monte Carlo (OKMC) technique. We evaluate the relevance of the underlying physical assumptions by applying the model to a large variety of irradiation experiments. Our model predictions are compared with new experimental data obtained with atom probe tomography and small angle neutron scattering, complemented with information from the literature. The results of this study reveal that the role of immobilized self-interstitial atoms (SIA) loops dominates the nucleation process of NSRC.

Published
2019

20. Multiscale modelling in nuclear ferritic steels: From nano-sized defects to embrittlement

Author

Castin, N., primary, Bonny, G., additional, Konstantinović, M.J., additional, Bakaev, A., additional, Bergner, F., additional, Courilleau, C., additional, Domain, C., additional, Gómez-Ferrer, B., additional, Hyde, J.M., additional, Messina, L., additional, Monnet, G., additional, Pascuet, M.I., additional, Radiguet, B., additional, Serrano, M., additional, and Malerba, L., additional

Published
2022
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23. Interaction of carbon with microstructural defects in a W-Re matrix: An ab initio assessment.

Author

Bakaev, A., Zinovev, A., Terentyev, D., Bonny, G., Yin, C., Castin, N., Mastrikov, Yu. A., and Zhurkin, E. E.

Subjects
EDGE dislocations, POINT defects, SCREW dislocations, CARBON, MATRICES (Mathematics)
Abstract

The interaction of carbon atoms with point defects and the core of edge and screw dislocations with Burgers vector a 0 / 2 ⟨ 111 ⟩ in W and a W-Re matrix is studied by means of ab initio calculations. The structure and energetics of the ground-state atomic configurations are presented and rationalized. It is found that di-vacancies, which are thermally unstable in pure W according to the state-of-the-art ab initio calculations, can nucleate at C and Re-C complexes, which fill the gap in the explanation of the emergence of nanovoids observed experimentally under irradiation. Also, on the basis of the recent experimental evidence and our calculations, the temperature ranges for the manifestation of the yield drop phenomenon, which is related to the obstruction of dislocation motion due to their decoration by impurities such as carbon, are revealed. [ABSTRACT FROM AUTHOR]

Published
2019
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32. Effect of statistically stored dislocations in tungsten on the irradiation induced nano-hardening analyzed by different methods

Author

UCL - SST/IMMC - Institute of Mechanics, Materials and Civil Engineering, Bonny, G., Khvan, T., Bakaeva, A., Yin, C., Dubinko, A., Cabet, C., Loyer-Prost, M., Castin, N., Bakaev, A., Terentyev, D., UCL - SST/IMMC - Institute of Mechanics, Materials and Civil Engineering, Bonny, G., Khvan, T., Bakaeva, A., Yin, C., Dubinko, A., Cabet, C., Loyer-Prost, M., Castin, N., Bakaev, A., and Terentyev, D.

Abstract

Tungsten self-ion irradiation was performed at 800 °C up to 0.01-1 dpa on two different W grades with essentially different dislocation density. Nanoindentation was applied to characterize the radiation hardening in two W grades with different microstructure. Different methods to analyze the indentation curves were applied to extract the bulk equivalent radiation hardening. It was shown that depending on the applied method, different outcomes may occur. The most satisfactory procedure was established and a consistent set of parameters was found. The bulk equivalent radiation hardening was found to saturate above 0.1 dpa. The characteristic distance between irradiation induced defects acting as dislocation pinning points was found to decrease up to 0.1 dpa, and then saturate/increase with irradiation dose. No essential difference in radiation hardening was observed between the studied W grades with essentially different initial dislocation density.

Published
2021

33. Multiscale modelling for fusion and fission materials: the M4F project

Author

Malerba, L., Caturla, M. J., Gaganidze, E., Kaden, C., Konstantinović, M. J., Olsson, P., Robertson, C., Rodney, D., Ruiz-Moreno, A. M., Serrano, M., Aktaa, J., Anento, N., Austin, S., Bakaev, A., Balbuena, J. P., Bergner, F., Boioli, F., Boleininger, M., Bonny, G., Castin, N., Chapman, J. B. J., Chekhonin, P., Clozel, M., Devincre, B., Dupuy, L., Diego, G., Dudarev, S. L., Fu, C. C., Gatti, R., Gélébart, L., Gómez-Ferrer, B., Gonçalves, D., Guerrero, C., Gueye, P. M., Hähner, P., Hannula, S. P., Hayat, Q., Hernández-Mayoral, M., Jagielski, J., Jennett, N., Jiménez, F., Kapoor, G., Kraych, A., Khvan, T., Kurpaska, L., Kuronen, A., Kvashin, N., Libera, O., Ma, P. W., Manninen, T., Marinica, M. C., Merino, S., Meslin, E., Mompiou, F., Mota, F., Namburi, H., Ortiz, C. J., Pareige, C., Prester, M., Rajakrishnan, R. R., Sauzay, M., Serra, A., Simonovski, I., Soisson, F., Spätig, P., Tanguy, D., Terentyev, D., Trebala, M., Trochet, M., Ulbricht, A., Vallet, M., Vogel, K., Yalcinkaya, T., Zhao, J., Malerba, L., Caturla, M. J., Gaganidze, E., Kaden, C., Konstantinović, M. J., Olsson, P., Robertson, C., Rodney, D., Ruiz-Moreno, A. M., Serrano, M., Aktaa, J., Anento, N., Austin, S., Bakaev, A., Balbuena, J. P., Bergner, F., Boioli, F., Boleininger, M., Bonny, G., Castin, N., Chapman, J. B. J., Chekhonin, P., Clozel, M., Devincre, B., Dupuy, L., Diego, G., Dudarev, S. L., Fu, C. C., Gatti, R., Gélébart, L., Gómez-Ferrer, B., Gonçalves, D., Guerrero, C., Gueye, P. M., Hähner, P., Hannula, S. P., Hayat, Q., Hernández-Mayoral, M., Jagielski, J., Jennett, N., Jiménez, F., Kapoor, G., Kraych, A., Khvan, T., Kurpaska, L., Kuronen, A., Kvashin, N., Libera, O., Ma, P. W., Manninen, T., Marinica, M. C., Merino, S., Meslin, E., Mompiou, F., Mota, F., Namburi, H., Ortiz, C. J., Pareige, C., Prester, M., Rajakrishnan, R. R., Sauzay, M., Serra, A., Simonovski, I., Soisson, F., Spätig, P., Tanguy, D., Terentyev, D., Trebala, M., Trochet, M., Ulbricht, A., Vallet, M., Vogel, K., Yalcinkaya, T., and Zhao, J.

Abstract

The M4F project brings together the fusion and fission materials communities working on the prediction of radiation damage production and evolution and its effects on the mechanical behaviour of irradiated ferritic/martensitic (F/M) steels. It is a multidisciplinary project in which several different experimental and computational materials science tools are integrated to understand and model the complex phenomena associated with the formation and evolution of irradiation induced defects and their effects on the macroscopic behaviour of the target materials. In particular the project focuses on two specific aspects: (1) To develop physical understanding and predictive models of the origin and consequences of localised deformation under irradiation in F/M steels; (2) To develop good practices and possibly advance towards the definition of protocols for the use of ion irradiation as a tool to evaluate radiation effects on materials. Nineteen modelling codes across different scales are being used and developed and an experimental validation programme based on the examination of materials irradiated with neutrons and ions is being carried out. The project enters now its 4th year and is close to delivering high-quality results. This paper overviews the work performed so far within the project, highlighting its impact for fission and fusion materials science.

Published
2021

34. Vacancy-solute clustering in Fe-Cr alloys after neutron irradiation

Author

Konstantinovic, M. J., Ulbricht, A., Brodziansky, T., Castin, N., and Malerba, L.

Subjects
Neutron irradiation, FeCr alloys and steels, FeCr alloys, Steels
Abstract

Vacancy-solute clustering in neutron irradiated Fe-Cr alloys with various concentrations of Cr and minor solutes (Ni, Si and P) were studied by using coincidence Doppler broadening spectroscopy and small angle neutron scattering techniques. The results from both experiments, supported by an object kinetic Monte Carlo model, show in a very consistent way the existence and formation of vacancy-CrNiSiP clusters that play detrimental role in irradiation hardening. Similar solute cluster number density of about 30 to 50 x10^16cm-3 and an average diameter of about 1 nm were estimated for all alloys containing minor solutes, irrespectively of the chromium content. In Fe9Cr ferritic and Fe9Cr ferritic/martensitic alloys, with significantly reduced concentration of minor solute elements, the main defects are vacancy clusters, with an average cluster size size of about 10 and 2 vacancies, respectively. Large concentration of alpha'-precipitates was observed in Fe14Cr(NiSiP). However, both vacancy clusters and alpha'-precipitates provide significantly less impact to hardening in comparison to vacancy-CrNiSiP clusters. The fact that vacancy clustering in Fe9Cr ferritic alloy resembles that of pure iron suggests that Cr solutes may play lesser role in irradiation hardening of ferritic alloys and steels than previously believed.

Published
2020

35. The dominating mechanisms for the formation of solute-rich clusters in steels under irradiation

Author

Castin, N., Bonny, G., Bakaev, A., (0000-0002-4058-1044) Bergner, F., Domain, C., Hyde, J. M., Messina, L., Radiguet, B., Riddle, N., (0000-0001-9161-7505) Malerba, L., Castin, N., Bonny, G., Bakaev, A., (0000-0002-4058-1044) Bergner, F., Domain, C., Hyde, J. M., Messina, L., Radiguet, B., Riddle, N., and (0000-0001-9161-7505) Malerba, L.

Abstract

The formation of nano-sized, coherent, solute-rich clusters (NSRC) is known to be an important factor causing the degradation of the macroscopic properties of steels under irradiation. The mechanisms driving their formation are still debated. This work focuses on low-Cu reactor pressure vessel (RPV) steels, where solute species are generally not expected to precipitate. We rationalize the processes that take place at the nanometer scale under irradiation, relying on the latest theoretical and experimental evidence on atomic-level diffusion and transport processes. These are compiled in a new model, based on the object kinetic Monte Carlo (OKMC) technique. We evaluate the relevance of the underlying physical assumptions by applying the model to a large variety of irradiation experiments. Our model predictions are compared with new experimental data obtained with atom probe tomography and small angle neutron scattering, complemented with information from the literature. The results of this study reveal that the role of immobilized self-interstitial atoms (SIA) loops dominates the nucleation process of NSRC.

Published
2020

36. Trends in vacancy distribution and hardness of high temperature neutron irradiated single crystal tungsten

Author

UCL - SST/IMMC - Institute of Mechanics, Materials and Civil Engineering, Bonny, G., Konstantinovic, M.J., Bakaeva, A., Yin, Chao, Castin, N., Mergia, K., Chatzikos, V., Dellis, S., Khvan, T., Bakaev, A., Dubinko, A., Terentyev, D., UCL - SST/IMMC - Institute of Mechanics, Materials and Civil Engineering, Bonny, G., Konstantinovic, M.J., Bakaeva, A., Yin, Chao, Castin, N., Mergia, K., Chatzikos, V., Dellis, S., Khvan, T., Bakaev, A., Dubinko, A., and Terentyev, D.

Abstract

The aim of the present study is to extend the knowledge about the formation and thermal stability of vacancy-type defects in tungsten under neutron irradiation, thereby mimicking the temperature and neutron flux expected in the ITER divertor. Neutron irradiation of single crystal tungsten, W(100), in the temperature range 600-1200 °C is performed up to 0.12 dpa. Positron annihilation spectroscopy is employed to detect the presence of open volume defects, while hardness tests are applied to relate the irradiation-induced defects with the modification of mechanical properties. Rationalization of the experimental results is enhanced by the application of a kinetic Monte Carlo simulation tool, applied to model the microstructural evolution under the neutron irradiation process. The relation between radiation microstructure and hardness is explained via a dispersed barrier model.

Published
2020

45. Influence of the specificities of ion irradiation on the nanostructural evolution in Fe alloys: an object kinetic Monte Carlo study

Author

Chiapetto, M., Malerba, L., Castin, N., Heintze, C., and Becquart, C. S.

Subjects
continuous irradiation, Physics::Medical Physics, ion irradiation, technology, industry, and agriculture, pulsed irradiation, kinetic Monte Carlo, Fe-Cr alloys
Abstract

This work investigates the nanostructural evolution under ion irradiation in both a binary Fe-C alloy and an Fe-9%Cr-C alloy at 300°C, using an object kinetic Monte Carlo model originally developed to simulate neutron irradiation in Fe-(Cr)-C alloys. We studied the effect of specificities of ion irradiation that are expected to have an impact on the evolution of radiation-induced defect clusters as compared to neutron irradiation. The most relevant impact is due to the difference in dose-rate between neutron and ion irradiation. Moreover, the effect of two different ion irradiation regimes (continuous versus pulsed) on the nanostructure evolution material was also investigated: the presence of Cr was seen to lead to a different response over accumulated dose, the reason having been identified in the defect cluster recombination mechanism.

Published
2017

46. Improved atomistic Monte Carlo models based on ab-initio-trained neural networks Application to FeCu and FeCr alloys

Author

Castin, N., Messina, L., Domain, C., Pasianot, Rc., Olsson, P., CEA-Direction des Energies (ex-Direction de l'Energie Nucléaire) (CEA-DES (ex-DEN)), and Commissariat à l'énergie atomique et aux énergies alternatives (CEA)

Subjects
to, Carlo, [PHYS.NUCL]Physics [physics]/Nuclear Theory [nucl-th], Application, FeCr, ab-initio-trained, FeCu, based, Monte, and, [PHYS.NEXP]Physics [physics]/Nuclear Experiment [nucl-ex], on, atomistic, models, Improved, alloys, networks, neural
Abstract

International audience; We significantly improve the physical models underlying atomistic Monte Carlo (MC) simulations, throughthe use of ab initio fitted high-dimensional neural network potentials (NNPs). In this way, we can incorporateenergetics derived from density functional theory (DFT) in MC, and avoid using empirical potentials that arevery challenging to design for complex alloys. We take significant steps forward from a recent work whereartificial neural networks (ANNs), exclusively trained on DFT vacancy migration energies, were used to performkinetic MC simulations of Cu precipitation in Fe. Here, a more extensive transfer of knowledge from DFTto our cohesive model is achieved via the fitting of NNPs, aimed at accurately mimicking the most importantaspects of the ab initio predictions. Rigid-lattice potentials are designed to monitor the evolution during thesimulation of the system energy, thus taking care of the thermodynamic aspects of the model. In addition,other ANNs are designed to evaluate the activation energies associated with the MC events (migration towardsfirst-nearest-neighbor positions of single point defects), thereby providing an accurate kinetic modeling. Becauseour methodology inherently requires the calculation of a substantial amount of reference data, we design as welllattice-free potentials, aimed at replacing the very costly DFT method with an approximate, yet accurate andconsiderably more computationally efficient, potential. The binary FeCu and FeCr alloys are taken as sampleapplications considering the extensive literature covering these systems.

Published
2017

49. Modeling the first stages of Cu precipitation in α-Fe using a hybrid atomistic kinetic Monte Carlo approach.

Author

Castin, N., Pascuet, M. I., and Malerba, L.

Subjects
*COPPER, *PRECIPITATION (Chemistry), *MONTE Carlo method, *IRON, *ALGORITHMS, *METAL clusters, *ARTIFICIAL neural networks
Abstract

We simulate the coherent stage of Cu precipitation in α-Fe with an atomistic kinetic Monte Carlo (AKMC) model. The vacancy migration energy as a function of the local chemical environment is provided on-the-fly by a neural network, trained with high precision on values calculated with the nudged elastic band method, using a suitable interatomic potential. To speed up the simulation, however, we modify the standard AKMC algorithm by treating large Cu clusters as objects, similarly to object kinetic Monte Carlo approaches. Seamless matching between the fully atomistic and the coarse-grained approach is achieved again by using a neural network, that provides all stability and mobility parameters for large Cu clusters, after training on atomistically informed results. The resulting hybrid algorithm allows long thermal annealing experiments to be simulated, within a reasonable CPU time. The results obtained are in very good agreement with several series of experimental data available from the literature, spanning over different conditions of temperature and alloy composition. We deduce from these results and relevant parametric studies that the mobility of Cu clusters containing one vacancy plays a central role in the precipitation mechanism. [ABSTRACT FROM AUTHOR]

Published
2011
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50. Calculation of proper energy barriers for atomistic kinetic Monte Carlo simulations on rigid lattice with chemical and strain field long-range effects using artificial neural networks.

Author

Castin, N. and Malerba, L.

Subjects
*MONTE Carlo method, *ARTIFICIAL neural networks, *CHROMIUM alloys, *REGRESSION analysis, *PHYSICAL & theoretical chemistry
Abstract

In this paper we take a few steps further in the development of an approach based on the use of an artificial neural network (ANN) to introduce long-range chemical effects and zero temperature relaxation (elastic strain) effects in a rigid lattice atomistic kinetic Monte Carlo (AKMC) model. The ANN is trained to predict the vacancy migration energies as calculated given an interatomic potential with the nudged elastic band method, as functions of the local atomic environment. The kinetics of a single-vacancy migration is thus predicted as accurately as possible, within the limits of the given interatomic potential. The detailed procedure to apply this method is described and analyzed in detail. A novel ANN training algorithm is proposed to deal with the necessarily large number of input variables to be taken into account in the mathematical regression of the migration energies. The application of the ANN-based AKMC method to the simulation of a thermal annealing experiment in Fe–20%Cr alloy is reported. The results obtained are found to be in better agreement with experiments, as compared to already published simulations, where no atomic relaxation was taken into account and chemical effects were only heuristically allowed for. [ABSTRACT FROM AUTHOR]

Published
2010
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