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1.	Chang, Zhongwen, et al. (author) Assessment of the dislocation bias in fcc metals and extrapolation to austenitic steels 2015 In: Journal of Nuclear Materials. - : Elsevier BV. - 0022-3115 .- 1873-4820. ; 465 Journal article (peer-reviewed)abstract A systematic study of dislocation bias has been performed using a method that combines atomistic and elastic dislocation-point defect interaction models with a numerical solution of the diffusion equation with a drift term. Copper, nickel and aluminium model lattices are used in this study, covering a wide range of shear moduli and stacking fault energies. It is found that the dominant parameter for the dislocation bias in fcc metals is the width of the stacking fault ribbon. The variation in elastic constants does not strongly impact the dislocation bias value. As a result of this analysis and its extrapolation, the dislocation bias of the widely applied austenitic stainless steels of 316 type is predicted to be about 0.1 at temperature close to the swelling peak (815 K) and typical dislocation density of 1014 m-2. This is in line with the bias calculated using the elastic interaction model, which implies that the prediction method can be used readily in other fcc systems even without EAM potentials. By comparing the bias values obtained using atomistic- and elastic interaction energies, about 20% discrepancy is found, therefore a more realistic bias value for the 316 type alloy is 0.08 in these conditions.

Chang, Zhongwen, et al. (author)
Assessment of the dislocation bias in fcc metals and extrapolation to austenitic steels
2015
In: Journal of Nuclear Materials. - : Elsevier BV. - 0022-3115 .- 1873-4820. ; 465
Journal article (peer-reviewed)abstract
- A systematic study of dislocation bias has been performed using a method that combines atomistic and elastic dislocation-point defect interaction models with a numerical solution of the diffusion equation with a drift term. Copper, nickel and aluminium model lattices are used in this study, covering a wide range of shear moduli and stacking fault energies. It is found that the dominant parameter for the dislocation bias in fcc metals is the width of the stacking fault ribbon. The variation in elastic constants does not strongly impact the dislocation bias value. As a result of this analysis and its extrapolation, the dislocation bias of the widely applied austenitic stainless steels of 316 type is predicted to be about 0.1 at temperature close to the swelling peak (815 K) and typical dislocation density of 1014 m-2. This is in line with the bias calculated using the elastic interaction model, which implies that the prediction method can be used readily in other fcc systems even without EAM potentials. By comparing the bias values obtained using atomistic- and elastic interaction energies, about 20% discrepancy is found, therefore a more realistic bias value for the 316 type alloy is 0.08 in these conditions.

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