Abstract
Understanding the morphological evolution of precipitates is critical for evaluating their hardening effects and therefore improving the yield strength of an alloy during aging. Here we present a three-dimensional phase-field model for capturing both the nucleation and the growth kinetics of the precipitates and apply it to modeling θ′ precipitates in 319 aluminum alloys. The model incorporates the relevant thermodynamic data, diffusion coefficients, and the anisotropic misfit strain from literature, together with the anisotropic interfacial energy from first-principles calculations. The modified classical nucleation theory is implemented to capture the nucleation kinetics. The model parameters are optimized by comparing the simulation results to the experimentally measured peak number density, average diameters, average thicknesses and volume fractions of precipitates during isothermal aging at 463 K (190 °C), 503 K (230 °C) and 533 K (260 °C). Further model improvements in terms of prediction accuracy of the precipitate kinetics in 319 alloys and the remaining challenges are discussed.
| Original language | English (US) |
|---|---|
| Pages (from-to) | 84-94 |
| Number of pages | 11 |
| Journal | Computational Materials Science |
| Volume | 151 |
| DOIs | |
| State | Published - Aug 2018 |
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All Science Journal Classification (ASJC) codes
- Computer Science(all)
- Chemistry(all)
- Materials Science(all)
- Mechanics of Materials
- Physics and Astronomy(all)
- Computational Mathematics
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Phase-field modeling of θ′ precipitation kinetics in 319 aluminum alloys. / Ji, Yanzhou; Ghaffari, Bita; Li, Mei; Chen, Long Qing.
In: Computational Materials Science, Vol. 151, 08.2018, p. 84-94.Research output: Contribution to journal › Article
TY - JOUR
T1 - Phase-field modeling of θ′ precipitation kinetics in 319 aluminum alloys
AU - Ji, Yanzhou
AU - Ghaffari, Bita
AU - Li, Mei
AU - Chen, Long Qing
PY - 2018/8
Y1 - 2018/8
N2 - Understanding the morphological evolution of precipitates is critical for evaluating their hardening effects and therefore improving the yield strength of an alloy during aging. Here we present a three-dimensional phase-field model for capturing both the nucleation and the growth kinetics of the precipitates and apply it to modeling θ′ precipitates in 319 aluminum alloys. The model incorporates the relevant thermodynamic data, diffusion coefficients, and the anisotropic misfit strain from literature, together with the anisotropic interfacial energy from first-principles calculations. The modified classical nucleation theory is implemented to capture the nucleation kinetics. The model parameters are optimized by comparing the simulation results to the experimentally measured peak number density, average diameters, average thicknesses and volume fractions of precipitates during isothermal aging at 463 K (190 °C), 503 K (230 °C) and 533 K (260 °C). Further model improvements in terms of prediction accuracy of the precipitate kinetics in 319 alloys and the remaining challenges are discussed.
AB - Understanding the morphological evolution of precipitates is critical for evaluating their hardening effects and therefore improving the yield strength of an alloy during aging. Here we present a three-dimensional phase-field model for capturing both the nucleation and the growth kinetics of the precipitates and apply it to modeling θ′ precipitates in 319 aluminum alloys. The model incorporates the relevant thermodynamic data, diffusion coefficients, and the anisotropic misfit strain from literature, together with the anisotropic interfacial energy from first-principles calculations. The modified classical nucleation theory is implemented to capture the nucleation kinetics. The model parameters are optimized by comparing the simulation results to the experimentally measured peak number density, average diameters, average thicknesses and volume fractions of precipitates during isothermal aging at 463 K (190 °C), 503 K (230 °C) and 533 K (260 °C). Further model improvements in terms of prediction accuracy of the precipitate kinetics in 319 alloys and the remaining challenges are discussed.
UR - http://www.scopus.com/inward/record.url?scp=85046747995&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85046747995&partnerID=8YFLogxK
U2 - 10.1016/j.commatsci.2018.04.051
DO - 10.1016/j.commatsci.2018.04.051
M3 - Article
AN - SCOPUS:85046747995
VL - 151
SP - 84
EP - 94
JO - Computational Materials Science
JF - Computational Materials Science
SN - 0927-0256
ER -