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Publications (10 of 75) Show all publications
Becquart, C. S., Ngayam Happy, R., Olsson, P. & Domain, C. (2018). A DFT study of the stability of SIAs and small SIA clusters in the vicinity of solute atoms in Fe. Journal of Nuclear Materials, 500, 92-109
Open this publication in new window or tab >>A DFT study of the stability of SIAs and small SIA clusters in the vicinity of solute atoms in Fe
2018 (English)In: Journal of Nuclear Materials, ISSN 0022-3115, E-ISSN 1873-4820, Vol. 500, p. 92-109Article in journal (Refereed) Published
Abstract [en]

The energetics, defect volume and magnetic properties of single SIAs and small SIA clusters up to size 6 have been calculated by DFT for different configurations like the parallel 〈110〉 dumbbell, the non parallel 〈110〉 dumbbell and the C15 structure. The most stable configurations of each type have been further analyzed to determine the influence on their stability of various solute atoms (Ti, V, Cr, Mn, Co, Ni, Cu, Mo, W, Pd, Al, Si, P), relevant for steels used under irradiation. The results show that the presence of solute atoms does not change the relative stability order among SIA clusters. The small SIA clusters investigated can bind to both undersized and oversized solutes. Several descriptors have been considered to derive interesting trends from results. It appears that the local atomic volume available for the solute is the main physical quantity governing the binding energy evolution, whatever the solute type (undersized or oversized) and the cluster configuration (size and type).

Place, publisher, year, edition, pages
Elsevier B.V., 2018
Keywords
Ab initio calculations, Fe alloys, Interstitial clusters, Interstitials, Radiation damage, Binding energy, Bins, Calculations, Iron alloys, Manganese, Palladium, Cluster configurations, Energy evolutions, Physical quantities, Relative stabilities, Stable Configuration, Atoms
National Category
Physical Sciences
Identifiers
urn:nbn:se:kth:diva-223123 (URN)10.1016/j.jnucmat.2017.12.022 (DOI)000425108100013 ()2-s2.0-85039432847 (Scopus ID)
Note

Export Date: 13 February 2018; Article; CODEN: JNUMA; Correspondence Address: Becquart, C.S.; Univ.Lille, CNRS, INRA, ENSCL, UMR 8207, UMET, Unité Matériaux et TransformationsFrance; email: charlotte.becquart@univ-lille1.fr; Funding details: 2016153636, PRACE, Partnership for Advanced Computing in Europe AISBL. QC 20180327

Available from: 2018-03-27 Created: 2018-03-27 Last updated: 2018-03-27Bibliographically approved
Castin, N., Pascuet, M. I., Messina, L., Domain, C., Olsson, P., Pasianot, R. C. & Malerba, L. (2018). Advanced atomistic models for radiation damage in Fe-based alloys: Contributions and future perspectives from artificial neural networks. Computational materials science, 148, 116-130
Open this publication in new window or tab >>Advanced atomistic models for radiation damage in Fe-based alloys: Contributions and future perspectives from artificial neural networks
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2018 (English)In: Computational materials science, ISSN 0927-0256, E-ISSN 1879-0801, Vol. 148, p. 116-130Article in journal (Refereed) Published
Abstract [en]

Machine learning, and more specifically artificial neural networks (ANN), are powerful and flexible numerical tools that can lead to significant improvements in many materials modelling techniques. This paper provides a review of the efforts made so far to describe the effects of irradiation in Fe-based and W-based alloys, in a multiscale modelling framework. ANN were successfully used as innovative parametrization tools in these models, thereby greatly enhancing their physical accuracy and capability to accomplish increasingly challenging goals. In the provided examples, the main goal of ANN is to predict how the chemical complexity of local atomic configurations, and/or specific strain fields, influence the activation energy of selected thermally-activated events. This is most often a more efficient approach with respect to previous computationally heavy methods. In a future perspective, similar schemes can be potentially used to calculate other quantities than activation energies. They can thus transfer atomic-scale properties to higher-scale simulations, providing a proper bridging across scales, and hence contributing to the achievement of accurate and reliable multiscale models.

Place, publisher, year, edition, pages
Elsevier, 2018
Keywords
Artificial neural networks, Kinetic Monte Carlo, Irradiation damage, Multiscale modelling
National Category
Materials Engineering
Identifiers
urn:nbn:se:kth:diva-226734 (URN)10.1016/j.commatsci.2018.02.025 (DOI)000428907600013 ()2-s2.0-85042355717 (Scopus ID)
Funder
EU, Horizon 2020, 755039, 661913
Note

QC 20180503

Available from: 2018-05-03 Created: 2018-05-03 Last updated: 2018-05-03Bibliographically approved
Bakaev, A., Terentyev, D., Chang, Z., Posselt, M., Olsson, P. & Zhurkin, E. E. (2018). Effect of isotropic stress on dislocation bias factor in bcc iron: an atomistic study. Philosophical Magazine, 98(1), 54-74
Open this publication in new window or tab >>Effect of isotropic stress on dislocation bias factor in bcc iron: an atomistic study
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2018 (English)In: Philosophical Magazine, ISSN 1478-6435, E-ISSN 1478-6443, Vol. 98, no 1, p. 54-74Article in journal (Refereed) Published
Abstract [en]

The effect of externally applied stress on the dislocation bias factor (BF) in bcc iron has been studied using a combination of atomistic static calculations and finite element integration. Three kinds of dislocations were considered, namely, a0/2〈1 1 1〉{1 1 0} screw, a0/2〈1 1 1〉{1 1 0} edge and a0〈1 0 0〉{0 0 1} edge dislocations. The computations reveal that the isotropic crystal expansion leads to an increasing or constant dislocation bias, depending on the Burgers vector and type of dislocation. On the other hand, compressive stress reduces the dislocation bias for all the dislocations studied. Variation of the dislocation BF depending on dislocation type and Burgers vector is discussed by analysing the modification of the interaction energy landscape and the capture efficiency values for the vacancy and self-interstitial atom. 

Place, publisher, year, edition, pages
Taylor and Francis Ltd., 2018
Keywords
dislocation bias factor, external stress, Ferritic steels, molecular statics, Compressive stress, Dislocations (crystals), Ferritic steel, Screw dislocations, Atomistic studies, Bias factor, Capture efficiency, Crystal expansion, Interaction energies, Self-interstitial atoms, Edge dislocations
National Category
Materials Engineering
Identifiers
urn:nbn:se:kth:diva-223184 (URN)10.1080/14786435.2017.1390325 (DOI)000428264800004 ()2-s2.0-85032657074 (Scopus ID)
Note

Export Date: 13 February 2018; Article; Correspondence Address: Bakaev, A.; Institute of Ion Beam Physics and Materials Research, Helmholtz-Zentrum Dresden-RossendorfGermany; email: abakaev@sckcen.be; Funding details: 604862, FP7, Seventh Framework Programme; Funding details: 633053, FP7, Seventh Framework Programme; Funding details: EC, European Commission

Available from: 2018-02-28 Created: 2018-02-28 Last updated: 2018-04-11Bibliographically approved
Castin, N., Messina, L., Domain, C., Pasianot, R. C. & Olsson, P. (2017). Improved atomistic Monte Carlo models based on ab-initio -trained neural networks: Application to FeCu and FeCr alloys. Physical Review B, 95(21), Article ID 214117.
Open this publication in new window or tab >>Improved atomistic Monte Carlo models based on ab-initio -trained neural networks: Application to FeCu and FeCr alloys
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2017 (English)In: Physical Review B, ISSN 2469-9950, E-ISSN 2469-9969, Vol. 95, no 21, article id 214117Article in journal (Refereed) Published
Abstract [en]

We significantly improve the physical models underlying atomistic Monte Carlo (MC) simulations, through the use of ab initio fitted high-dimensional neural network potentials (NNPs). In this way, we can incorporate energetics derived from density functional theory (DFT) in MC, and avoid using empirical potentials that are very challenging to design for complex alloys. We take significant steps forward from a recent work where artificial neural networks (ANNs), exclusively trained on DFT vacancy migration energies, were used to perform kinetic MC simulations of Cu precipitation in Fe. Here, a more extensive transfer of knowledge from DFT to our cohesive model is achieved via the fitting of NNPs, aimed at accurately mimicking the most important aspects of the ab initio predictions. Rigid-lattice potentials are designed to monitor the evolution during the simulation 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 towards first-nearest-neighbor positions of single point defects), thereby providing an accurate kinetic modeling. Because our methodology inherently requires the calculation of a substantial amount of reference data, we design as well lattice-free potentials, aimed at replacing the very costly DFT method with an approximate, yet accurate and considerably more computationally efficient, potential. The binary FeCu and FeCr alloys are taken as sample applications considering the extensive literature covering these systems.

Place, publisher, year, edition, pages
American Physical Society, 2017
National Category
Physical Sciences
Identifiers
urn:nbn:se:kth:diva-216439 (URN)10.1103/PhysRevB.95.214117 (DOI)000404465700001 ()2-s2.0-85023764914 (Scopus ID)
Note

QC 20171208

Available from: 2017-12-08 Created: 2017-12-08 Last updated: 2017-12-08Bibliographically approved
Bonny, G., Bakaev, A., Olsson, P., Domain, C., Zhurkin, E. E. & Posselt, M. (2017). Interatomic potential to study the formation of NiCr clusters in high Cr ferritic steels. Journal of Nuclear Materials, 484, 42-50
Open this publication in new window or tab >>Interatomic potential to study the formation of NiCr clusters in high Cr ferritic steels
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2017 (English)In: Journal of Nuclear Materials, ISSN 0022-3115, E-ISSN 1873-4820, Vol. 484, p. 42-50Article in journal (Refereed) Published
Abstract [en]

Under irradiation NiSiPCr clusters are formed in high-Cr ferritic martensitic steels as well as in FeCr model alloys. In the literature little is known about the origin and contribution to the hardening of these clusters. In this work we performed density functional theory (DFT) calculations to study the stability of small substitutional NiCr-vacancy clusters and interstitial configurations in bcc Fe. Based on DFT data and experimental considerations a ternary potential for the ferritic FeNiCr system was developed. The potential was applied to study the thermodynamic stability of NiCr clusters by means of Metropolis Monte Carlo (MMC) simulations. The results of our simulations show that Cr and Ni precipitate as separate fractions and suggest only a limited synergetic effect between Ni and Cr. Therefore our results suggest that the NiCrSiP clusters observed in experiments must be the result of other mechanisms than the synergy of Cr and Ni at thermal equilibrium.

Place, publisher, year, edition, pages
Elsevier, 2017
Keywords
Alloy steel, Density functional theory, Ferrite, Martensitic steel, Monte Carlo methods, Nickel, Radiation damage, Thermodynamic stability, Ferritic-martensitic steels, High Cr ferritic steel, Interatomic potential, Metropolis Monte Carlo, Model alloys, Synergetic effect, Thermal equilibriums, Vacancy cluster, Ferritic steel
National Category
Physical Sciences
Identifiers
urn:nbn:se:kth:diva-201940 (URN)10.1016/j.jnucmat.2016.11.017 (DOI)000393246300006 ()2-s2.0-85006062721 (Scopus ID)
Note

QC 20170307

Available from: 2017-03-07 Created: 2017-03-07 Last updated: 2017-11-29Bibliographically approved
Messina, L., Castin, N., Domain, C. & Olsson, P. (2017). Introducing ab initio based neural networks for transition-rate prediction in kinetic Monte Carlo simulations. Physical Review B, 95(6), Article ID 064112.
Open this publication in new window or tab >>Introducing ab initio based neural networks for transition-rate prediction in kinetic Monte Carlo simulations
2017 (English)In: Physical Review B, ISSN 2469-9950, E-ISSN 2469-9969, Vol. 95, no 6, article id 064112Article in journal (Refereed) Published
Abstract [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.

National Category
Condensed Matter Physics
Identifiers
urn:nbn:se:kth:diva-207991 (URN)10.1103/PhysRevB.95.064112 (DOI)000395988200003 ()2-s2.0-85014555517 (Scopus ID)
Note

QC 20170607

Available from: 2017-06-07 Created: 2017-06-07 Last updated: 2017-11-29Bibliographically approved
Schuler, T., Lopes, D. A., Claisse, A. & Olsson, P. (2017). Transport properties of C and O in UN fuels. Physical Review B, 95(9), Article ID 094117.
Open this publication in new window or tab >>Transport properties of C and O in UN fuels
2017 (English)In: Physical Review B, ISSN 2469-9950, E-ISSN 2469-9969, Vol. 95, no 9, article id 094117Article in journal (Refereed) Published
Abstract [en]

Uranium nitride fuel is considered for fast reactors (GEN-IV generation and space reactors) and for light water reactors as a high-density fuel option. Despite this large interest, there is a lack of information about its behavior for in-pile and out-of-pile conditions. From the present literature, it is known that C and O impurities have significant influence on the fuel performance. Here we perform a systematic study of these impurities in the UN matrix using electronic-structure calculations of solute-defect interactions and microscopic jump frequencies. These quantities were calculated in the DFT+U approximation combined with the occupation matrix control scheme, to avoid convergence to metastable states for the 5f levels. The transport coefficients of the system were evaluated with the self-consistent mean-field theory. It is demonstrated that carbon and oxygen impurities have different diffusion properties in the UN matrix, with O atoms having a higher mobility, and C atoms showing a strong flux coupling anisotropy. The kinetic interplay between solutes and vacancies is expected to be the main cause for surface segregation, as incorporation energies show no strong thermodynamic segregation preference for (001) surfaces compared with the bulk.

Place, publisher, year, edition, pages
AMER PHYSICAL SOC, 2017
National Category
Physical Sciences
Identifiers
urn:nbn:se:kth:diva-206699 (URN)10.1103/PhysRevB.95.094117 (DOI)000399216100001 ()2-s2.0-85016234987 (Scopus ID)
Note

QC 20170509

Available from: 2017-05-09 Created: 2017-05-09 Last updated: 2017-11-29Bibliographically approved
Messina, L., Chiapetto, M., Olsson, P., Becquart, C. S. & Malerba, L. (2016). An object kinetic Monte Carlo model for the microstructure evolution of neutron-irradiated reactor pressure vessel steels. Paper presented at Conference on Advances in Materials and Processing Technologies (AMPT), DEC 14-17, 2015, Carlos III Univ, Leganes, SPAIN. Physica Status Solidi (a) applications and materials science, 213(11), 2974-2980
Open this publication in new window or tab >>An object kinetic Monte Carlo model for the microstructure evolution of neutron-irradiated reactor pressure vessel steels
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2016 (English)In: Physica Status Solidi (a) applications and materials science, ISSN 1862-6300, E-ISSN 1862-6319, Vol. 213, no 11, p. 2974-2980Article in journal (Refereed) Published
Abstract [en]

This work presents a full object kinetic Monte Carlo framework for the simulation of the microstructure evolution of reactor pressure vessel (RPV) steels. The model pursues a "gray-alloy" approach, where the effect of solute atoms is seen exclusively as a reduction of the mobility of defect clusters. The same set of parameters yields a satisfactory evolution for two different types of alloys, in very different irradiation conditions: an Fe-C-MnNi model alloy (high flux) and a high-Mn, high-Ni RPV steel (low flux). A satisfactory match with the experimental characterizations is obtained only if assuming a substantial immobilization of vacancy clusters due to solute atoms, which is here verified by means of independent atomistic kinetic Monte Carlo simulations. The microstructure evolution of the two alloys is strongly affected by the dose rate; a predominance of single defects and small defect clusters is observed at low dose rates, whereas larger defect clusters appear at high dose rates. In both cases, the predicted density of interstitial loops matches the experimental solute-cluster density, suggesting that the MnNi-rich nanofeatures might form as a consequence of solute enrichment on immobilized small interstitial loops, which are invisible to the electron microscope.

Place, publisher, year, edition, pages
Wiley-VCH Verlagsgesellschaft, 2016
Keywords
crystal defects impurities, ferritic alloys, kinetic Monte Carlo simulations, neutron irradiation
National Category
Materials Engineering
Identifiers
urn:nbn:se:kth:diva-197781 (URN)10.1002/pssa.201600038 (DOI)000388323200029 ()2-s2.0-84992602797 (Scopus ID)
Conference
Conference on Advances in Materials and Processing Technologies (AMPT), DEC 14-17, 2015, Carlos III Univ, Leganes, SPAIN
Note

QC 20161228

Available from: 2016-12-28 Created: 2016-12-08 Last updated: 2017-11-29Bibliographically approved
Messina, L., Nastar, M., Sandberg, N. & Olsson, P. (2016). Systematic electronic-structure investigation of substitutional impurity diffusion and flux coupling in bcc iron. Physical Review B, 93(18), Article ID 184302.
Open this publication in new window or tab >>Systematic electronic-structure investigation of substitutional impurity diffusion and flux coupling in bcc iron
2016 (English)In: Physical Review B, ISSN 2469-9950, Vol. 93, no 18, article id 184302Article in journal (Refereed) Published
Abstract [en]

The diffusion properties of a wide range of impurities (transition metals and Al, Si, and P) in ferritic alloys are here investigated by means of a combined ab initio-atomic diffusion theory approach. The flux-coupling mechanisms and the solute-diffusion coefficients are inferred from electronic-structure calculations of solute-defect interactions and microscopic jump frequencies. All properties except the second-nearest-neighbor binding energy are found to have a characteristic bell shape as a function of the d-band filling for the 4d and 5d series, and an M shape for the 3d row because of the out-of-trend behavior of Mn. The solute jump frequencies are governed by compressibility, which makes diffusion of large solutes faster, although this effect is partially compensated for by lower attempt frequencies and larger correlations with the vacancy. Diffusion coefficients are predicted in a wide temperature range, far below the experimentally accessible temperatures. In accordance with experiments, Co is found to be a slow diffuser in iron, and the same behavior is predicted for Re, Os, and Ir impurities. Finally, flux-coupling phenomena depend on the iron jump frequencies next to a solute atom, which are mainly controlled by similar electronic interactions to those determining the binding energies. Vacancy drag and solute enrichment at sinks systematically arise below a solute-dependent temperature threshold, directly correlated with the electronic-level interactions at the equilibrium and the saddle-point states. Early transition metals with repulsive second-nearest-neighbor interactions also diffuse via vacancy drag, although they show a lower temperature threshold than the late metals. This confirms that drag is the most common solute-vacancy coupling mechanism in iron at low temperatures, and this is likely to be confirmed as well for impurity diffusion in other transition metals.

Place, publisher, year, edition, pages
American Physical Society, 2016
Keywords
Pressure-Vessel Steels, Initio Molecular-Dynamics, Atom-Probe Tomography, Augmented-Wave Method, Transition-Metals, Model Alloys, High-Nickel, 1st-Principles Calculations, Ultrasoft Pseudopotentials, Positron-Annihilation
National Category
Condensed Matter Physics
Identifiers
urn:nbn:se:kth:diva-187784 (URN)10.1103/PhysRevB.93.184302 (DOI)000375528000002 ()2-s2.0-84966429112 (Scopus ID)
Funder
Vattenfall ABGöran Gustafsson Foundation for Research in Natural Sciences and Medicine
Note

QC 20160530

Available from: 2016-05-30 Created: 2016-05-30 Last updated: 2016-05-30Bibliographically approved
Chang, Z., Terentyev, D., Sandberg, N., Samuelsson, K. & Olsson, P. (2015). Anomalous bias factors of dislocations in bcc iron. Journal of Nuclear Materials, 461, 221-229
Open this publication in new window or tab >>Anomalous bias factors of dislocations in bcc iron
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2015 (English)In: Journal of Nuclear Materials, ISSN 0022-3115, E-ISSN 1873-4820, Vol. 461, p. 221-229Article in journal (Refereed) Published
Abstract [en]

Dislocation bias factors in bcc Fe have been calculated based on atomistic interaction energy maps on three kinds of dislocations, namely the a0/2〈1 1 1〉{1 1 0} screw, a0/2〈1 1 1〉{1 1 0} and a0〈1 0 0〉{0 0 1} edge dislocations. The results show that the dislocation bias is higher for the a0/2〈1 1 1〉 edge dislocation than for the a0〈1 0 0〉 edge dislocation, even though the latter possesses a larger Burgers vector. This indicates the importance of the dislocation core contribution. For the a0/2〈1 1 1〉{1 1 0} screw dislocation, a negative dislocation bias has been obtained, which implies a more efficient absorption of vacancies than of SIAs. The effect of coexistence of both edge- and screw dislocations are assessed by a total bias. A possible complementary mechanism for explaining the long swelling incubation time in bcc metals is suggested and discussed.

Place, publisher, year, edition, pages
Elsevier, 2015
Keywords
Screw dislocations, Screws, Atomistic interactions, Bcc iron, Bcc metals, Bias factor, Complementary mechanisms, Dislocation core, Edge and screw dislocations, Incubation time
National Category
Metallurgy and Metallic Materials
Identifiers
urn:nbn:se:kth:diva-163276 (URN)10.1016/j.jnucmat.2015.03.025 (DOI)000355023900030 ()2-s2.0-84925678083 (Scopus ID)
Funder
EU, FP7, Seventh Framework Programme, (MatISSE project) 604862
Note

QC 20150331

Available from: 2015-03-31 Created: 2015-03-31 Last updated: 2017-12-04Bibliographically approved
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ORCID iD: ORCID iD iconorcid.org/0000-0002-2381-3309

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