2015
DOI: 10.1016/j.jnucmat.2015.09.054
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Grain boundary diffusion of Ag through polycrystalline SiC in TRISO fuel particles

Abstract: The effective diffusivity and release fraction of Ag in polycrystalline SiC are evaluated using a kinetic Monte Carlo model. The effects of various grain boundary network properties on the transport of Ag across the SiC layer have been examined, including fraction of grain boundary type, spread in grain boundary diffusivities and distribution of grain boundary types. It is shown that the effective diffusivity and release fraction of Ag can exhibit a large variability due to changes in the GB structure of SiC, … Show more

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Cited by 16 publications
(7 citation statements)
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“…It is important to note that the Ag diffusion through a pc-SiC may depend not only on the diffusivity in a given GB but also on the microstructure topology, particularly how the GB types are connected to form a network. In this work we focus on estimating D in HEGBs, a specific type of GB, and no model of mesoscale diffusion through a GB network is considered (please see Refs [29,30] for mesoscale transport models). However, since the HEGBs form a percolating network, if they are found to a fast diffusion path we expect these mesoscale effects on the overall measured diffusion coefficient and its activation energy to be relatively minor [29].…”
Section: Introductionmentioning
confidence: 99%
See 1 more Smart Citation
“…It is important to note that the Ag diffusion through a pc-SiC may depend not only on the diffusivity in a given GB but also on the microstructure topology, particularly how the GB types are connected to form a network. In this work we focus on estimating D in HEGBs, a specific type of GB, and no model of mesoscale diffusion through a GB network is considered (please see Refs [29,30] for mesoscale transport models). However, since the HEGBs form a percolating network, if they are found to a fast diffusion path we expect these mesoscale effects on the overall measured diffusion coefficient and its activation energy to be relatively minor [29].…”
Section: Introductionmentioning
confidence: 99%
“…In this work we focus on estimating D in HEGBs, a specific type of GB, and no model of mesoscale diffusion through a GB network is considered (please see Refs [29,30] for mesoscale transport models). However, since the HEGBs form a percolating network, if they are found to a fast diffusion path we expect these mesoscale effects on the overall measured diffusion coefficient and its activation energy to be relatively minor [29]. Therefore, in this work we will make direct comparisons between our calculated D values for the HEGB and experimentally measured D values from pc-SiC samples.…”
Section: Introductionmentioning
confidence: 99%
“…6(c) indicates that the elastic precursor compresses the material from 3.21 g/cm 3 to 4.21 g/cm 3 . The transformation shock wave additionally densifies the material to 4.91 g/cm 3 , which amounts to a 24% volume reduction at the strong elastic compression and an additional 14% volume reduction at the structural transformation. The total volume reduction at the strong shock at 4.0 km/s generated by the solid-solid transformation therefore amounts to 35%.…”
Section: Resultsmentioning
confidence: 99%
“…SiC is a well-known high strength ceramic material with outstanding properties that have been used in a wide range of applications, in particular, those involving extreme conditions of pressure, temperature, and wear such as in nuclear reactor cladding, [1][2][3] abrasives, 4 and gas turbines. 5 Owing to the low density and high strength, SiC is also an ideal material for armor.…”
Section: Introductionmentioning
confidence: 99%
“…In order to understand the mechanism(s) of Ag release, extensive studies, including out-of-pile release measurements from irradiated TRISO fuel [3][4][5][6], surrogate Ag diffusion experiments [7][8][9][10][11], and computer simulations [12][13][14][15] have been performed. While diffusion coefficients measured in laboratory diffusion couple experiments are in a very good agreement with values predicted by computer simulations, these diffusion coefficients are orders of magnitude lower than those observed in actual fuel release experiments.…”
Section: Introductionmentioning
confidence: 99%