2020
DOI: 10.1016/j.intermet.2020.106745
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Phase-field modeling of γ/γ″ microstructure formation in Ni-based superalloys with high γ″ volume fraction

Abstract: The excellent mechanical properties of the Ni-based superalloy IN718 mainly result from coherent γ precipitates. Due to a strongly anisotropic lattice misfit between the matrix and the precipitate phase, the particles exhibit pronounced plate-shaped morphologies. Using a phase-field model, we investigate various influencing factors that determine the equilibrium shapes of γ precipitates, minimizing the sum of the total elastic and interfacial energy. Upon increasing precipitate phase fractions, the model predi… Show more

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Cited by 23 publications
(20 citation statements)
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“…With respect to the boundaries, we apply periodic boundary conditions for all fields. To account for volume change of the simulation domain, we apply non-volume-conserving boundary conditions [ 5 ].…”
Section: Methodsmentioning
confidence: 99%
See 3 more Smart Citations
“…With respect to the boundaries, we apply periodic boundary conditions for all fields. To account for volume change of the simulation domain, we apply non-volume-conserving boundary conditions [ 5 ].…”
Section: Methodsmentioning
confidence: 99%
“…Diffusivities of the individual alloying elements are taken from the Dictra database MOBNi4. The interfacial energy is assumed to be isotropic and is estimated from ripening data and from the size dependent aspect ratio of the precipitates respectively [ 5 , 35 , 36 , 37 ].…”
Section: Methodsmentioning
confidence: 99%
See 2 more Smart Citations
“…Mesoscale approaches may seem more appealing to achieve larger length and time scales [ 34 , 35 ]. The meso-scale phase-field approach has also recently been employed to simulate shape formation of plate-like precipitates [ 36 ]. Li and Chen [ 37 ] simulated stress-oriented nucleation and growth of θ′ precipitates using two parabolic functions to describe the chemical free energies for the θ′- and α-phases.…”
Section: Introductionmentioning
confidence: 99%