The influence of temperature and storage time at RT on nucleation of the β″ phase in a 6082 Al–Mg–Si alloy

Marioara, Calin Daniel; Andersen, Sigmund Jarle; Jansen, J.C.; Zandbergen, H.W.

doi:10.1016/s1359-6454(02)00470-6

Cited by 326 publications

(161 citation statements)

References 12 publications

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“…The diffusion of a substitutional species i usually occurs via a vacancymediated process and so depends on the vacancy concentration c V and the migration enthalpy barrier [4][5][6][7] , with a diffusion coefficient ~ / . Control of aging is thus possible, in principle, by control of the available vacancy concentration c V .…”

Section: Introductionmentioning

confidence: 99%

Microalloying for the controllable delay of precipitate formation in metal alloys

Francis

2016

Acta Materialia

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A model is presented to predict the effectiveness of dilute solutes in delaying precipitate formation, with application to natural and artificial aging in metal alloys. Control of aging is achieved via the binding, at natural aging temperatures, and release, at artificial aging temperatures, of excess quenched vacancies by the solute atoms. The binding of vacancies to the solute atoms reduces the vacancy concentration in the bulk lattice, and thus reduces the rate of transport processes that control aging. To be useful, this strategy requires sufficiently strong, but not too strong, vacancy-solute binding, and sufficiently slow vacancy-solute diffusion, both quantified through application of the model. First-principles methods are used to compute the controlling materials properties (vacancy-solute binding energies and migration barrier) for a range of solutes in Al and Mg, and Pauli Electronegativity of the solute relative to the host metal is found useful for correlating properties. With the computed inputs, the model is applied to representative solutes (Ga, Sn, Pb) in Al that span weak to strong vacancy binding. Predictions of the model to Sn in Al are then shown to qualitatively agree with experiments, with quantitative agreement possible using a slightly stronger Sn-vacancy binding energy. The general model should be useful for identifying promising dilute solutes for control of precipitation/aging across many alloys in which quenched vacancies are used to control precipitation.

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Section: Introductionmentioning

confidence: 99%

Microalloying for the controllable delay of precipitate formation in metal alloys

Francis

2016

Acta Materialia

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“…The influence of prior natural ageing time on the subsequent artificial ageing response of Al-MgSi wrought alloys has been an interesting topic and has attracted a lot of research interest [3,[12][13][14][15][16]. In the 6000 series alloys with high alloying element concentrations, clusters formed during natural ageing have been considered to be "robust" during subsequent artificial ageing [1,12].…”

Section: Introductionmentioning

confidence: 99%

Solute nanostructures and their strengthening effects in Al–7Si–0.6Mg alloy F357

et al. 2012

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The solute-nanostructures formed in the primary α-Al grains of a Semi-Solid Metal cast Al-7Si-0.6Mg alloy (F357) during ageing at 180°C, and the age-hardening response of the alloy have been systematically investigated using transmission electron microscopy, atom probe tomography and hardness testing. A 120-h natural pre-ageing led to the formation of solute clusters and GP zones. The natural pre-ageing slowed down the precipitation kinetics six-fold during 1 h ageing at 180°C, but this effect diminished after 4 h when the sample reached the same hardness as that without the pre-ageing treatment. It reduced the number density of β″-needles to approximately half of that formed in samples without the treatment, and postponed the peak hardness occurrence to 4 h, 4 times that of the as-quenched sample. A hardness plateau developed in the as-quenched sample between 1 h and 4 h ageing corresponds to the growth of 2 the β″ precipitates and a significant concurrent decrease of solute clusters and GP zones. The average Mg:Si ratio of early solute clusters is < 0.7 while that of GP zones changes from 0.8 to 0.9 with increasing in their size, and that of β″-needles increases from 0.9 to 1.2. β″-needles, GP zones and solute clusters are important strengthening solute nanostructures of the alloy. The partitioning of solutes and precipitation kinetics of the alloy are discussed in detail.

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“…At the symmetry surfaces 1 11 0 when either 0 or 0 22x A Dirichlet condition cannot by applied at infinity as the solution unfortunately degenerates singularly on a cuboid domain, i.e. the solution has to become constant on a sphere as it fades out (this is an odd-dimensional property of the Laplace equation and is also the case for the analytical spheroid solutions above).…”

Section: Correction Factor From Numerical Diffusion Solution For Cuboidsmentioning

confidence: 99%

“…The formation of an equilibrium precipitate phase is preceded by a series of metastable nonspherical ones due to their ease of nucleation and anisotropies in their misfit strain energy, interfacial energy and attachment kinetics. Examples includes needle β'' precipitates in AlMg-Si [1], plate θ' precipitates in Al-Cu [2], platelet η' precipitates in Al-Zn-Mg [3], and lath S-family of precipitates in Al-Cu-Mg alloys [4]. Non-spherical precipitates are beneficial as they contribute to larger peak hardness via their effective blockage to dislocation motion [5].…”

Section: Introductionmentioning

confidence: 99%

Precipitation of Non-Spherical Particles in Aluminum Alloys Part I: Generalization of the Kampmann–Wagner Numerical Model

Holmedal

Osmundsen

2015

Metall Mater Trans A

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Particles precipitated during aging treatments often have non-spherical shapes, e.g. needles or plates, while in the classical Kampmann-Wagner Numerical (KWN) precipitation model it is assumed that the particles are of spherical shape. This model is here generalized resulting in two correction factors accounting for the effects induced by the particles' non-spherical shape on their growth kinetics. The first one is for the correction of the growth rate. It is derived from the approximate solution of the diffusion problem on spheroidal coordinate and verified by the three-dimensional numerical solutions for cuboid particles. The second factor is for the energetic correction due to the particle surface curvature. It is derived from chemical potential equality (or Gibbs energy minimization principle) at equilibrium for non-spherical particles and provides a correction factor for the Gibbs-Thomson effect. In the accompanying paper the two correction factors are implemented into a multi-component KWN modelling framework and the resulting improvements on the model's predictive power are demonstrated.

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The influence of temperature and storage time at RT on nucleation of the β″ phase in a 6082 Al–Mg–Si alloy

Cited by 326 publications

References 12 publications

Microalloying for the controllable delay of precipitate formation in metal alloys

Microalloying for the controllable delay of precipitate formation in metal alloys

Solute nanostructures and their strengthening effects in Al–7Si–0.6Mg alloy F357

Precipitation of Non-Spherical Particles in Aluminum Alloys Part I: Generalization of the Kampmann–Wagner Numerical Model

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