Grain growth in thin films with a fibre texture studied by phase-field simulations and mean field modelling

Moelans, Nele; Spaepen, Frans; Wollants, Patrick

doi:10.1080/14786430902998129

Cited by 23 publications

(24 citation statements)

References 53 publications

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“…Only at junctions where three or more grain boundaries intersect, a finite contribution is neglected by omitting the dependence of . The results in Table I and other applications of the model 37,63 show that the theoretical equilibrium angles at triple junctions are well reproduced, if the resolution of the numerical technique is high enough. Nevertheless, it remains to be analyzed in more detail if and to which extent restrictions ͑56a͒-͑56c͒ affect, for example, the kinetic behavior of multijunctions in the simulations.…”

Section: E Difficulties Of a Fully Variational Approach With Respectmentioning

confidence: 52%

Quantitative analysis of grain boundary properties in a generalized phase field model for grain growth in anisotropic systems

2008

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A good choice of model formulation and model parameters is one of the most important and difficult aspects in mesoscale modeling and requires a systematic and quantitative analysis. In this paper, it is studied how the model parameters of a generalized phase field model affect the landscape of the free-energy density functional, the phase field profiles at the grain boundaries, and the corresponding trajectory along the free-energy landscape. The analysis results in quantitative relations between the model parameters, on one hand, and grain boundary energy and mobility, on the other hand. Based on these findings, a procedure is derived that generates a suitable set of model parameters that reproduces accurately a material's grain boundary energy and mobility for arbitrary misorientation and inclination dependence. The misorientation and inclination dependence are formulated so that the diffuse interface width is constant, resulting in uniform stability and accuracy conditions for the numerical solution. The proposed model formulation and parameter choice allow us to perform quantitative simulations with excellent controllability of the numerical accuracy and therefore of the material behavior.

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Section: E Difficulties Of a Fully Variational Approach With Respectmentioning

confidence: 52%

Quantitative analysis of grain boundary properties in a generalized phase field model for grain growth in anisotropic systems

2008

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“…The paper [1] modified and combined the two kinetic modeling frameworks from [14,22] as applied to the particular case of polycrystalline thin films with so-called fiber textures. In this sufficiently narrow case, grains have nearly identical orientations in the axial direction perpendicular to a considered film, but random radial orientations in the plane of the film; see also [18]. In comparison with [14], the dependence of the kinetic model on large-scale simulations was essentially decreased.…”

Section: Introductionmentioning

confidence: 96%

“…In this situation, the further reduction in the interface energy can be reached only by decreasing the total measure of grain boundaries; see, for instance, [8,9]. Important statistical descriptors of grain boundary networks are misorientation distribution functions (often referred to as grain boundary character distributions), which show relative measures of interfaces with given misorientation parameters; see [1,[9][10][11][12][13][14][15][16][17][18][19][20][21][22][23][24]. In order to investigate how the structure and time evolution of misorientation distribution functions depend on the grain boundary energy anisotropy and set of laws governing the dynamics at a microscopic scale, it is possible to conduct numerical experiments via well-known large-scale simulation approaches.…”

Section: Introductionmentioning

confidence: 99%

“…In order to investigate how the structure and time evolution of misorientation distribution functions depend on the grain boundary energy anisotropy and set of laws governing the dynamics at a microscopic scale, it is possible to conduct numerical experiments via well-known large-scale simulation approaches. In particular, these are Monte Carlo methods [10][11][12][13][14], phase field models [12,17,18,25], curvature-driven grain growth models [19][20][21], level set methods [23,24], vertex models [26][27][28], etc. An alternative way is to develop kinetic models which are based on differential equations and, therefore, can be more computationally efficient, while focusing only on a restricted amount of essential characteristics.…”

Section: Introductionmentioning

confidence: 99%

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A kinetic approach to modeling general-texture evolution in two-dimensional polycrystalline grain growth

Yegorov

Emelianenko

2016

Computational Materials Science

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Important statistical descriptors of grain boundary networks are misorientation distribution functions (often referred to as grain boundary character distributions), which show relative measures of interfaces with given misorientation parameters. This paper is aimed at extending the Boltzmann-type kinetic modeling framework developed in the previous work [1] to the two-dimensional case of general textures with no restrictions on possible grain orientations, but under the assumption that the grain boundary energy density depends only on the disorientation variable. In order to avoid an enormous computational complexity of treating the general-texture case, the kinetic model for polycrystalline grain growth is constructed from the very beginning in a specific discretized form with respect to the disorientation variable. A significant aspect of the developed approach is that its formulation requires a collection of a priori distributions which describe possible disorientations of grain boundaries connected in a triple junction. A separate numerical algorithm for approximating such distributions is proposed as applied to cubic crystal lattices. The numerical results obtained by the constructed model are in good agreement with the corresponding large-scale simulation results from the related literature.

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“…The phase field model, on the other hand, is able to handle the complex geometry of microstructures since interfaces are diffuse and their motion can be characterized without explicit kinetic laws. Because of this advantage, the phase field method has been widely applied to model the grain growth in bulk materials [12][13][14][15][16][17][18][19][20][21][22][23][24]. It was shown that the phase field model is capable of revealing various characteristics of grain growth such as the evolution of average grain size and grain size distribution.…”

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confidence: 99%

Phase field modeling of grain growth in thin films on rigid substrates

Deng

2011

Physica Status Solidi (b)

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A phase field model of grain growth in thin films on rigid substrates is presented, in which the motion of grain boundaries is driven by curvatures as well as anisotropy in surface, interface, and strain energies. The match between the proposed model and the corresponding sharp interface model is demonstrated by asymptotic analysis. The effect of diffuse interface on grain boundary mobility is minimized. The parameters in the model are connected to the measurable properties of materials, and therefore can be obtained from experiments or atomic scale simulations. In numerical simulations, the influence of the texture dependent surface, interface, and strain energies on grain growth is illustrated. The effects of film thickness, strain level, and grain boundary grooving on grain size distribution and texture evolution are also investigated. The effectiveness as well as the limits of the present model are discussed, and the ways to extend it are proposed.

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Grain growth in thin films with a fibre texture studied by phase-field simulations and mean field modelling

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Cited by 23 publications

References 53 publications

Quantitative analysis of grain boundary properties in a generalized phase field model for grain growth in anisotropic systems

Quantitative analysis of grain boundary properties in a generalized phase field model for grain growth in anisotropic systems

A kinetic approach to modeling general-texture evolution in two-dimensional polycrystalline grain growth

Phase field modeling of grain growth in thin films on rigid substrates

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