Modeling over-ageing in Al-Mg-Si alloys by a multi-phase CALPHAD-coupled Kampmann-Wagner Numerical model

Du, Qiang; Tang, Kai; Marioara, Calin Daniel; Andersen, Sigmund Jarle; Holmedal, Bjørn; Holmestad, Randi

doi:10.1016/j.actamat.2016.09.052

Cited by 70 publications

(40 citation statements)

References 36 publications

(65 reference statements)

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“…The employed modeling approach is the CALculation PHAse Diagram (CALPHA)-coupled multi-component multi-phase Kampmann-Wagner numerical (KWN) approach reported by Du and his co-authors in a series of publications [17,[29][30][31][32][33]. The model predictions on the isothermal homogenization soaking and ageing heat treatment of Al alloys had been validated by the experimental microstructure characterizations.…”

Section: Accepted Manuscriptmentioning

confidence: 99%

Modelling and experimental validation of microstructure evolution during the cooling stage of homogenization heat treatment of Al–Mg–Si alloys

Lou

Tang

et al. 2018

Materialia

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A CALPHAD-coupled multi-component multi-phase Kampmann-Wagner Numerical modelling framework has been adapted and coupled with a homogenization model to predict the competitive nucleation and growth of multi-sized metastable/stable phase particles during the cooling stage of a homogenization heat treatment. The reported model is the continuation of our previous work on the homogenization soaking modelling [Du et al, Acta Materialia 61 (2013) 4961-4973]. It takes the experimentally verified soaking modelling prediction results as the initial microstructural status and predicts the microstructural evolution during the very last step of the homogenization treatment, i.e. the final cooling process. The model has been applied to two Al-Mg-Si alloys: AA6061 and AA6082. The simulation shows a multi-modal MgSi particle size distribution forms due to multiple nucleation events. For the AA6082 alloy the multiple nucleation events occur mainly due to the local micro-chemistry variations along a dendrite while for AA6061 it is due to the two opposite contributions to supersaturation: the positive contribution by the cooling and the negative contribution by the particles' growth. The interaction of intergranular and intragranular MgSi containing particles have been captured, and the partitioning of Mg and Si solutes among the two different sized MgSi particles has been predicted. The model predictions are in reasonable agreement with the microstructure characterization results obtained with Scanning Electron Microscopy (SEM), Transmission Electron Microscopy (TEM) and Electrical Resistivity Measurement on the quenched samples from some dedicated laboratory-scale homogenization heat treatment experiments. It is concluded that the extended KWN modelling framework is applicable to predict the microstructure evolution during the non-isothermal heat treatment of

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Section: Accepted Manuscriptmentioning

confidence: 99%

Modelling and experimental validation of microstructure evolution during the cooling stage of homogenization heat treatment of Al–Mg–Si alloys

Lou

Tang

et al. 2018

Materialia

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“…Simulation of sequential precipitations is at the cutting-edge of modeling phase precipitations. The approaches employed by Perez and Deschamps [51] and Du et al [52] can be adopted and expanded/built upon with the new understanding gained from studying the mechanism(s) of the ''abnormal'' size formation. The current TC-PRISMA code cannot handle sequential precipitations partly due to limited understanding of the processes.…”

Section: Opportunity To Collect Large Datasets On Phase Transformamentioning

confidence: 99%

High-Throughput and Systematic Study of Phase Transformations and Metastability Using Dual-Anneal Diffusion Multiples

Zhao

2020

Metall Mater Trans A

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This article highlights the capabilities of dual-anneal diffusion multiples (DADMs) in performing high-throughput and systematic studies of phase transformations and metastability. DADMs create wide ranges of solid solution compositions through elemental interdiffusion during a first anneal at a high temperature. After quenching to ambient temperature, each diffusion multiple can be cut into several slices, and each slice is further annealed individually at a lower/second temperature. Phase transformations take place in the supersaturated regions of the solid solution compositions that are formed during the first anneal, leading to various precipitates due to different driving force, interfacial energy, and other factors as composition varies across the regions in the sample. By subjecting the sliced diffusion multiples individually to different anneal durations and different second anneal temperatures, very large datasets can be collected on phase transformation kinetics and evolution of precipitate morphology as a function of composition, time, and temperature. Metastable phases and their transitions to more stable phases have been systematically observed in the Fe-Cr-Mo ternary system across a wide range of composition, temperature, and anneal time, thus providing a large amount of information on metastability of the phases. The solvi of the metastable and stable phases can be systematically collected for more reliable CALPHAD assessments of the Gibbs free energy of the metastable phases. By adjusting the interfacial energy value in simulations using models such as the Kampmann-Wagner Numerical (KWN) model and matching the simulated precipitate sizes at different compositions with experimentally measured sizes of the corresponding compositions in a DADM, the interfacial energy value can be obtained. Opportunities and challenges in using DADMs to collect large datasets on precipitation kinetics and morphology will be explained to enable full utilization of the capabilities of DADMs in the future. This review not only presents experimental results collected to date, but also explains the vast more datasets that can be collected from DADMs in the future. An approach that iteratively and holistically integrates experimental results with model predictions is advocated as a very effective means to advance the understanding of various phase transformation mechanisms. In this way, the new mechanistic understanding can be integrated to more robust models to simulate the ''abnormal'' behaviors that are observed in DADMs, especially related to sequential precipitations of phases that are common in engineering alloys. Examples are also shown to illustrate the systematic nature of DADMs as a result of their continuously varying composition regions in catching unusual phenomena and emergent trends that are easily missed during studies using discrete compositions afforded by individual alloys.

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“…The computational cost is also limiting in PF, especially when it is supposed to be used in CMD. In this case, macroscopic types of approaches like the Langer-Schwartz-Kampmann-Wagner (LSKW) [29] approach for precipitation modelling have the advantages that they can account concomitantly for nucleation, growth and coarsening of a distribution of precipitates, are fully coupled with CALPHAD databases and have been applied to numerous complex alloy systems, showing promising results [30][31][32]. However, the precipitation behaviour in multicomponent grades requires major attention because of the complex interconnection between capillary effects and diffusion fluxes couplings [33].…”

Section: Introductionmentioning

confidence: 99%

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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Modeling over-ageing in Al-Mg-Si alloys by a multi-phase CALPHAD-coupled Kampmann-Wagner Numerical model

Cited by 70 publications

References 36 publications

Modelling and experimental validation of microstructure evolution during the cooling stage of homogenization heat treatment of Al–Mg–Si alloys

Modelling and experimental validation of microstructure evolution during the cooling stage of homogenization heat treatment of Al–Mg–Si alloys

High-Throughput and Systematic Study of Phase Transformations and Metastability Using Dual-Anneal Diffusion Multiples

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

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