[HTML][HTML] Barrier-free predictions of short-range ordering/clustering kinetics in binary FCC solid solutions
Acta Materialia, 2023•Elsevier
We present comparisons of kinetic Monte Carlo (kMC) simulations of isothermal short-range
ordering (SRO) and clustering (SRC) kinetics in binary FCC alloys with a mean-field
concentration wave (CW) model. We find that the CW model is able to give order-of-
magnitude agreement with kMC simulations for ordering/clustering relaxation times over a
wide range of temperatures and compositions. The advantage of the CW model is that it
does not require parameterization of vacancy hopping energy barriers, which, for a …
ordering (SRO) and clustering (SRC) kinetics in binary FCC alloys with a mean-field
concentration wave (CW) model. We find that the CW model is able to give order-of-
magnitude agreement with kMC simulations for ordering/clustering relaxation times over a
wide range of temperatures and compositions. The advantage of the CW model is that it
does not require parameterization of vacancy hopping energy barriers, which, for a …
Abstract
We present comparisons of kinetic Monte Carlo (kMC) simulations of isothermal short-range ordering (SRO) and clustering (SRC) kinetics in binary FCC alloys with a mean-field concentration wave (CW) model. We find that the CW model is able to give order-of-magnitude agreement with kMC simulations for ordering/clustering relaxation times over a wide range of temperatures and compositions. The advantage of the CW model is that it does not require parameterization of vacancy hopping energy barriers, which, for a concentrated alloy, becomes prohibitive. We assess limits in the accuracy of the model, and discuss the effect of cooling rates as well as the extension to multi-component systems. Ultimately, the simplicity and performance of the CW model compared to kMC simulations suggests that it is a useful tool to connect with models of properties dependent on SRO/SRC as well as for designing thermal treatments to control formation of SRO/SRC.
Elsevier
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