Multi-Objective Optimization of the Nanocavities Diffusion in Irradiated Metals

Backer, Andrée De; Souidi, Abdelkader; Hodille, E.; Autissier, Emmanuel; Genevois, Cécile; Haddad, Farah; Noce, Antonin Della; Domain, Christophe; Becquart, Charlotte; Barthe, Marie-France

doi:10.3390/psf2022005041

Cited by 1 publication

(4 citation statements)

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“…Finally, n, the number of vacancies in the object, and s, the visible defect size (diameter), are related by the expression s n a 3 π n 1 3 . The results of the multi-objective optimisation of the diffusion temperatures led to two diffusion parameter sets labelled up and low, as briefly explained in Supplementary Section S5 of the Supplementary Material and in detail in De Backer et al (2022) and De Backer et al (2023). The up (resp.…”

Section: The Diffusion Of the Nanocavitiesmentioning

confidence: 99%

“…The up and low sets are our upper and lower limit estimates of the parameters. The ref sets are the parameters fixed for the multi-objective optimisation which give the up and down diffusion in De Backer et al (2022) and De Backer et al (2023). The possibility "no diffusion," diff no, and a source term with only Frenkel pairs, ST fp, has been added.…”

Section: Sensitivity Analysis Of the Modelmentioning

confidence: 99%

“…We then tried to limit the number of simulations while sufficiently exploring the high-dimension space of input parameters. To estimate the sensitivity, we were informed by the multi-objective function defined in De Backer et al (2022) and De Backer et al (2023). We therefore defined an objective function ranging from 0 to 1.…”

Section: Sensitivity Analysis Of the Modelmentioning

confidence: 99%

“…We emphasise the uncertainty estimation, providing upper and lower limits of the parameter sets. The method we used to obtain the diffusion coefficients of the nanocavities with multi-objective optimisation is detailed in De Backer et al (2022) and De Backer et al (2023). In the fourth section, we describe a sensitivity analysis based on systematically combining upper and lower parameter sets.…”

Section: Introductionmentioning

confidence: 99%

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Readdressing nanocavity diffusion in tungsten

De Backer,

Souidi,

Hodille

et al. 2023

Front. Nucl. Eng.

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In nuclear fusion (ITER and the future DEMO), those components that face the plasma are exposed to high temperature and irradiation which, in the long term, modifies their thermal and mechanical properties and tritium retention. Tungsten is a candidate material and is the subject of many studies of microstructure evolution under various irradiation and temperature conditions. One milestone is the characterization of its defect properties. We here readdress the diffusion of nanocavities on broad ranges of size and temperature and compare it with dissociation, a competing process during nanocavity growth. First, at the atomic scale, we used molecular dynamics to explore the variety of elementary events involved in the nanocavity diffusion. Second, an experimental study of ion-irradiated samples, annealed at different temperatures up to 1,773 K, revealed the creation and growth of nanocavities on transmission electron microscopy images. Third, we performed multi-objective optimization of the nanocavity diffusion input of our object kinetic Monte Carlo model to reproduce the experimental results. Finally, we applied a sensitivity analysis of the main inputs of our model developed for these particular conditions—the source term which combines two cascade databases and the impurities whose interaction with the defects is characterised with a supplemented database of density functional theory calculations. Three domains of nanocavity size were observed. The first is the small vacancy clusters, for which atomistic calculations are possible and dissociation is negligible. The second is the small nanocavities, for which we provide new diffusion data and where a competition with the dissociation can take place. The third domain is the large nanocavities, for which, in any case, the dissociation prevents their existence above 1,500 K in the absence of a stabilizing interface.

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Section: The Diffusion Of the Nanocavitiesmentioning

confidence: 99%

Section: Sensitivity Analysis Of the Modelmentioning

confidence: 99%

Section: Sensitivity Analysis Of the Modelmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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