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Condensed Matter > Materials Science
Title: An Experimentally Informed Continuum Grain Boundary Model
(Submitted on 25 Jan 2022 (v1), last revised 26 Jan 2024 (this version, v3))
Abstract: A continuum grain boundary model is developed that uses experimentally measured grain boundary energy data as a function of misorientation to simulate idealized grain boundary evolution in a 1-D grain array. The model uses a continuum representation of the misorientation in terms of spatial gradients of the orientation as a fundamental field. The grain boundary energy density employed is non-convex in this orientation gradient, based on physical grounds. Simple gradient descent dynamics of the energy are utilized for idealized microstructure evolution, which requires higher-order regularization of the energy density for the model to be well-set; the regularization is physically justified. Microstructure evolution is presented using two plausible energy density functions, both defined from the same experimental data: a 'smooth' and a 'cusp' energy density. Results of grain boundary equilibria and microstructure evolution representing grain reorientation in one space dimension are presented. The different shapes of the energy density functions representing a common data set are shown to result in different overall microstructural evolution of the system. Mathematically, the constructed energy functional formally is of the Aviles-Giga/Cross-Newell type but with unequal well-depths, resulting in a difference in the structural feature of solutions that can be identified with grain boundaries, as well as in the approach to equilibria from identical initial conditions. This study also investigates the metastability of grain boundaries. It supports the general thermodynamics belief that they persist for extended periods before eventually vanishing due to the lowest energy configuration favored by fluctuations over infinite time.
Submission history
From: Alankar Alankar [view email][v1] Tue, 25 Jan 2022 02:50:44 GMT (6863kb)
[v2] Mon, 7 Feb 2022 18:00:59 GMT (6718kb,D)
[v3] Fri, 26 Jan 2024 04:41:03 GMT (8759kb,D)
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