Modeling Cu precipitation in tempered martensitic steels

Yang, Jinbo; Enomoto, Masato; Zhang, C.

doi:10.1016/j.msea.2006.02.003

Cited by 24 publications

(2 citation statements)

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“…However, the precipitation behaviour in multicomponent grades requires major attention because of the complex interconnection between capillary effects and diffusion fluxes couplings [33]. Prior works using LSKW precipitation modelling have been performed on binary Fe-Cu alloys and multicomponent steels with Cu precipitation [30,34,35]. For example, Stechauner et al [35] modelled Cu precipitation in a Fe-Cu binary system, and the results were in good agreement with experimental details.…”

Section: Introductionmentioning

confidence: 85%

“…For example, Stechauner et al [35] modelled Cu precipitation in a Fe-Cu binary system, and the results were in good agreement with experimental details. Furthermore, Yang et al [34] developed and applied a numerical model to simulate Cu precipitation in the Fe-C-Mn-Cu quaternary system, showing reasonable results by comparing with experimental works. Even though the modelling efforts in the literature have shown promising results, it appears as if one aspect has not been studied in detail.…”

Section: Introductionmentioning

confidence: 92%

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Langer–Schwartz–Kampmann–Wagner precipitation simulations: assessment of models and materials design application for Cu precipitation in PH stainless steels

et al. 2020

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Quantitative modelling of precipitation kinetics can play an important role in a computational material design framework where, for example, optimization of alloying can become more efficient if it is computationally driven. Precipitation hardening (PH) stainless steels is one example where precipitation strengthening is vital to achieve optimum properties. The Langer–Schwartz–Kampmann–Wagner (LSKW) approach for modelling of precipitation has shown good results for different alloy systems, but the specific models and assumptions applied are critical. In the present work, we thus apply two state-of-the-art LSKW tools to evaluate the different treatments of nucleation and growth. The precipitation modelling is assessed with respect to experimental results for Cu precipitation in PH stainless steels. The LSKW modelling is able to predict the precipitation during ageing in good quantitative agreement with experimental results if the nucleation model allows for nucleation of precipitates with a composition far from the equilibrium and if a composition-dependent interfacial energy is considered. The modelling can also accurately predict trends with respect to alloy composition and ageing temperature found in the experimental data. For materials design purposes, it is though proposed that the modelling is calibrated by measurements of precipitate composition and fraction in key experiments prior to application. Graphic abstract

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