Atomistic simulations of Be irradiation on W: mixed layer formation and erosion

Lasa, A.; Heinola, K.; Nordlund, K.

doi:10.1088/0029-5515/54/8/083001

Cited by 11 publications

(11 citation statements)

References 36 publications

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“…While many potentials exist for tungsten 32 , only one exists for modeling W and Be 33 , which is a Tersoff style bond order potential (BOP) 10 . This potential has been used to study both beryllium implantation in tungsten 34 and mixed beryllium-deuterium implantation in tungsten 35 . However, this potential form is not robust enough to capture the complex interactions between tungsten, beryllium, and their intermetallic structures.…”

Section: Introductionmentioning

confidence: 99%

Data-driven material models for atomistic simulation

et al. 2019

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The central approximation made in classical molecular dynamics simulation of materials is the interatomic potential used to calculate the forces on the atoms. Great effort and ingenuity is required to construct viable functional forms and find accurate parameterizations for potentials using traditional approaches. Machinelearning has emerged as an effective alternative approach to develop accurate and robust interatomic potentials. Starting with a very general model form, the potential is learned directly from a database of electronic structure calculations and therefore can be viewed as a multiscale link between quantum and classical atomistic simulations. Risk of inaccurate extrapolation exists outside the narrow range of time-and length-scales where the two methods can be directly compared. In this work, we use the Spectral Neighbor Analysis Potential (SNAP) and show how a fit can be produced with minimal interpolation errors which is also robust in extrapolating beyond training. To demonstrate the method, we have developed a new tungsten-beryllium potential suitable for the full range of binary compositions. Subsequently, large-scale molecular dynamics simulations were performed of high energy Be atom implantation onto the (001) surface of solid tungsten. The new machine learned W-Be potential generates a population of implantation structures consistent with quantum calculations of defect formation energies. A very shallow (< 2nm) average Be implantation depth is predicted which may explain ITER diverter degradation in the presence of beryllium.

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Section: Introductionmentioning

confidence: 99%

Data-driven material models for atomistic simulation

et al. 2019

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“…The substrate for the cumulative D impacts was formed depositing Be with 50 eV on W (3000 Be impacts, at normal incidence). A detailed description of this material mixing is given in [10]. The W-Be mixture was repeatedly quenched (heated up to 1000 K and cooled down to 500 K) until the system was energetically stable.…”

Section: Methodsmentioning

confidence: 99%

“…Further, an empirical scaling equation was suggested describing the influence of the co-deposition conditions (surface temperature, incident particle energy and flux) on the D retention [8]. However, computational work is scarce, only consisting of Monte Carlo simulations on the erosion of W and carbon exposed to Beseeded D plasmas [9], molecular dynamics (MD) modelling of W-Be mixed layer formation [10] and Be erosion from Be 2 W surfaces under D irradiation [11], and a comparison between binary collision approximation (BCA) [12] and MD simulations on the mixed layer erosion [13].…”

Section: Introductionmentioning

confidence: 99%

The effect of beryllium on deuterium implantation in tungsten by atomistic simulations

2014

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Tungsten (W) and beryllium (Be) have been chosen as plasma-facing materials for the ITER reactor and the main fuel component will be deuterium (D). Due to plasma–wall interactions, these materials will immediately mix via erosion, transport and re-deposition. We present the first atomistic study on the effect of D co-implanted with Be into W, by modelling D plus Be irradiation of W surfaces, at projectile energies and compositions relevant for the plasma–wall interactions. The D implantation and Be sticking yields increased with the Be fraction in the system, especially at the lowest energies, as a Be layer was deposited on the surface. Tungsten was sputtered by Be, although the yield was partially suppressed by the deposited Be–D layer, and the Be erosion was determined by the balance between the Be concentration at the surface and projectile energy. Molecules were also sputtered: a large fraction of the D is reflected as D2, and purely metallic molecules (Be2, BeW) as well as different Be–D compounds were sputtered. On the other hand, the D clustered when implanted in or beneath a pre-deposited Be–W layer.

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“…There are a limited number of first principle based atomistic calculations available in the literature [3,16,22,[36][37][38][39] to understand the Be-W thermodynamics and surface interactions. There are also a number of molecular statics and dynamics simulations available in the literature [16,21,22,[40][41][42][43][44][45][46] to understand the kinetics of beryllium-tungsten intermetallic layer formation and growth. Chen's latest work [47], as well as Bjorkas' and Lasa's simulations focused on erosion and mixing through energetic ion implantation: irradiation of tungsten by beryllium, of mixed Be-W by deuterium, and of tungsten by D-Be.…”

Section: Modeling Be-w Interactionsmentioning

confidence: 99%

Assessment of the literature about Be-W mixed material layer formation in the fusion reactor environment

Lasa,

Dasgupta,

Baldwin

et al. 2024

Mater. Res. Express

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All plasma facing surfaces in a fusion reactor, whether initially pure or an alloy, will rapidly evolve into a mixed material due to plasma-induced erosion, migration and redeposition. Beryllium (Be) erosion from the main chamber, and its transport and deposition on to a tungsten (W) divertor results in the growth of mixed Be-W layers, which can evolve to form beryllides. These Be-W mixed materials exhibit generally less desirable properties than pure tungsten or pure beryllium, such as lower melting points. In order to better understand the parameter space for growth of these alloys, this paper reviews the literature on Be-W mixed material formation experiments – in magnetically confined fusion reactors, in linear plasma test stands, and during thin- film deposition – and on computational modeling of Be-W interactions, as well as briefly assesses the Be-W growth kinetics. We conclude that the following kinetic steps drive the material mixing: adsorption of the implanted/deposited ion on the metal surface; diffusion of the implanted/deposited ion from surface into the bulk, which is accelerated by defects; and loss of deposited material through erosion. Adsorption dominates (or prevents) material mixing in thin-film deposition experiments, whereas diffusion drives material mixing in plasma exposures due to the energetic ion implantation.

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Atomistic simulations of Be irradiation on W: mixed layer formation and erosion

Cited by 11 publications

References 36 publications

Data-driven material models for atomistic simulation

Data-driven material models for atomistic simulation

The effect of beryllium on deuterium implantation in tungsten by atomistic simulations

Assessment of the literature about Be-W mixed material layer formation in the fusion reactor environment

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