Overview No. 124 Modelling of precipitation reactions in industrial processing

Bratland, D.; Grong, Ø.; Shercliff, Hugh; Myhr, Ole Runar; Tjøtta, Stig

doi:10.1016/s1359-6454(96)00100-0

Cited by 161 publications

(115 citation statements)

References 34 publications

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“…It is observed that the predicted sizes of the S phase precipitates correspond very well with the measured sizes: deviations are within about 4% and are almost equal to the standard errors of the average size measurements. Table 2 The measured mean equivalent diameters of end-on S precipitates as obtained from TEM The model: achievements and limitations: Modelling of microstructural changes using the KW model has been applied in a range of papers [9][10]35,37], and in some works strength predictions have also been made [2][3][4][5][6]. However in these previous works the assessment of the model was usually limited to comparison with only strength data and/or precipitate size data.…”

Section: Resultsmentioning

confidence: 99%

“…The equations (4) and (7) represent an approximation (ignoring the Zeldovitch factor [38]) that has been applied in previous works [2,5,9,10] with some success, but it can be refined further to take into account more detailed theories of the atomic attachment rate and the Zeldovich factor [3,4,35]. In the KW model the nucleated precipitates can only grow if their size is greater than the critical size [3,19,].…”

Section: Nucleation Of S Phasementioning

confidence: 99%

“…There has been considerable interest in the modelling of precipitation kinetics and strengthening in age hardening aluminium alloys [1,2,3,4,5,6,7,8,9,10,11,12,13]. Most of the published work on modelling of the precipitation kinetics in aluminium alloys is based on two main approaches [1][2][3][4][5][6][7][8][9][10].…”

Section: Introductionmentioning

confidence: 99%

“…Most of the published work on modelling of the precipitation kinetics in aluminium alloys is based on two main approaches [1][2][3][4][5][6][7][8][9][10]. In one of the approaches, the modelling of the nucleation, growth and impingement of precipitates are based on the concepts of the Johnson-Mehl-AvramiKolmogorov (JMAK) model [14,15,16] and the modelling of the coarsening kinetics is based on the Lifshitz-Slyozov-Wagner (LSW) theory [17,18].…”

Section: Introductionmentioning

confidence: 99%

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A model for precipitation kinetics and strengthening in Al–Cu–Mg alloys

Khan

Starink

Yan

2008

Materials Science and Engineering: A

133

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A physically-based numerical model is developed to predict the microstructural evolution and strengthening in Al-Cu-Mg alloys during isothermal treatments. The modelling of the formation kinetics of the precipitates is based on the Kampmann and Wagner model. The strengthening by the shearable Cu:Mg co-clusters is modelled on the basis of modulus strengthening mechanism and the strengthening by the non-shearable S phase precipitates is based on the Orowan looping mechanism. The model predictions are verified by comparing with the strength and differential isothermal calorimetery data on 2024-T351 aluminium alloys. The microstructural development and strength predictions of the model are generally in good agreement with the experimental data.

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Section: Resultsmentioning

confidence: 99%

Section: Nucleation Of S Phasementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

A model for precipitation kinetics and strengthening in Al–Cu–Mg alloys

Khan

Starink

Yan

2008

Materials Science and Engineering: A

133

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“…[1][2][3] Because the former strength contribution is by far the most important one, the precipitation sequence and resulting strength evolution occurring during natural and artificial aging of the alloys have been extensively investigated and reported upon in the scientific literature. [4][5][6] In addition, the chemical composition and atomic structure of the clusters and hardening precipitate which form have been studied in detail by means of various high-resolution experimental techniques along with atomistic modeling.…”

Section: Introductionmentioning

confidence: 99%

An Extended Age-Hardening Model for Al-Mg-Si Alloys Incorporating the Room-Temperature Storage and Cold Deformation Process Stages

Myhr

Grong

Schäfer

2015

Metall Mater Trans A

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In this article, a new age-hardening model for Al-Mg-Si alloys is presented (named NaMo-Version 2), which takes into account the combined effect of cold deformation and prolonged room-temperature storage on the subsequent response to artificial aging. As a starting point, the original physical framework of NaMo-Version 1 is revived and used as a basis for the extension. This is permissible, since a more in-depth analysis of the underlying particle-dislocation interactions confirms previous expectations that the simplifying assumption of spherical precipitates is not crucial for the final outcome of the calculations, provided that the yield strength model is calibrated against experimental data. At the same time, the implementation of the Kampmann-Wagner formalism means that the different microstructure models can be linked together in a manner that enforces solute partitioning and competition between the different hardening phases which form during aging (e.g., clusters, b¢¢ and b¢). In a calibrated form, NaMo-Version 2 exhibits a high degree of predictive power, as documented by comparison with experiments, using both dedicated nanostructure and yield strength data as a basis for the validation. Hence, the model is deemed to be well-suited for simulation of thermomechanical processing of Al-Mg-Si alloys involving cold-working operations like sheet forming and stretch bending in combination with heat treatment and welding.

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Homogeneous Second‐Phase Precipitation

Wagner

Kampmann²,

Voorhees

2013

Materials Science and Technology

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The sections in this article are Introduction General Considerations General Course of an Isothermal Precipitation Reaction Thermodynamic Considerations–Metastability and Instability Decomposition Mechanisms: Nucleation and Growth versus Spinodal Decomposition Thermodynamic Driving Forces for Phase Separation Experimental Techniques for Studying Decomposition Kinetics Microanalytical Tools Direct Imaging Techniques Scattering Techniques Experimental Problems Influence of Quenching Rate on Kinetics Distinction of the Mode of Decomposition Precipitate Morphologies Experimental Results Factors Controlling the Shapes and Morphologies of Precipitates Early Stage Decomposition Kinetics Cluster‐Kinetics Approach Classical Nucleation–Sharp Interface Model Time‐Dependent Nucleation Rate Experimental Assessment of Classical Nucleation Theory Non‐Classical Nucleation–Diffuse Interface Model Distinction Between Classical and Non‐Classical Nucleation Diffusion‐Controlled Growth of Nuclei from the Supersaturated Matrix The Cluster‐Dynamics Approach to Generalized Nucleation Theory Spinodal Theories The Philosophy of Defining a ‘Spinodal Alloy' —Morphologies of ‘Spinodal Alloys' Monte Carlo Studies Coarsening of Precipitates General Remarks The LSW Theory of Coarsening Extensions of the Coarsening Theory to Finite Precipitate Volume Fractions Other Approaches Towards Coarsening Influence of Coherency Strains on the Mechanism and Kinetics of Coarsening–Particle Splitting Numerical Approaches Treating Nucleation, Growth and Coarsening as Concomitant Processes General Remarks on the Interpretation of Experimental Kinetic Data of Early Decomposition Stages The Langer and S chwartz Theory ( LS Model) and its Modification by K ampmann and W agner ( MLS Model) The Numerical Model ( N Model) of K ampmann and W agner ( KW ) Decomposition of a Homogeneous Solid Solution General Course of Decomposition Comparison Between the MLS Model and the N Model The Appearance and Experimental Identification of the Growth and Coarsening Stages Extraction of the Interfacial Energy and the Diffusion Constant from Experimental Data Decomposition Kinetics in Alloys Pre‐Decomposed During Quenching Influence of the Loss of Particle Coherency on the Precipitation Kinetics Combined Cluster‐Dynamic and Deterministic Description of Decomposition Kinetics Self‐Similarity, Dynamical Scaling and Power‐Law Approximations Dynamical Scaling Power‐Law Approximations Non‐Isothermal Precipitation Reactions Acknowledgements

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Overview No. 124 Modelling of precipitation reactions in industrial processing

Cited by 161 publications

References 34 publications

A model for precipitation kinetics and strengthening in Al–Cu–Mg alloys

A model for precipitation kinetics and strengthening in Al–Cu–Mg alloys

An Extended Age-Hardening Model for Al-Mg-Si Alloys Incorporating the Room-Temperature Storage and Cold Deformation Process Stages

Homogeneous Second‐Phase Precipitation

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