Large Scale Statistics for Computational Verification of Grain Growth Simulations with Experiments
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Large Scale Statistics for Computational Verification of Grain Growth Simulations with Experiments Melik C. Demirel1,2,3, Andrew P. Kuprat2, Denise C. George2, Galen K. Straub2, Amit Misra3, Kathleen Alexander3, and Anthony D. Rollett1 1
Carnegie Mellon University, Department of Materials Science & Engineering, PA, USA Theoretical Division, T-1, Los Alamos National Laboratory, NM, USA 3 Materials Science and Technology, MST-8, Los Alamos National Laboratory, NM, USA 2
ABSTRACT It is known that by controlling microstructural development, desirable properties of materials can be achieved. The main objective of our research is to understand and control interface dominated material properties, and finally, to verify experimental results with computer simulations. We have previously showed a strong similarity between small-scale grain growth experiments and anisotropic three-dimensional simulations obtained from the Electron Backscattered Diffraction (EBSD) measurements [1]. Using the same technique, we obtained 5170-grain data from an Aluminum-film (120µm thick) with a columnar grain structure. Experimentally obtained starting microstructure and grain boundary properties are input for the three-dimensional grain growth simulation. In the computational model, minimization of the interface energy is the driving force for the grain boundary motion. The computed evolved microstructure is compared with the final experimental microstructure, after annealing at 550 ºC. INTRODUCTION Characterization of the structures and properties of grain boundary networks (GBN) to produce desirable microstructures is one of the fundamental problems in interface science. There is an ongoing research for the development of new experimental and analytical techniques in order to obtain and synthesize information related to GBN ([2]; [3]; [4]). The grain boundary energy and mobility data were characterized by Electron Backscattered Diffraction (EBSD) technique and Atomic Force Microscopy (AFM) observations (i.e., for ceramic MgO [5] and for the metal Al [6]). Grain boundary energies are extracted from triple junction (TJ) geometry considering the local equilibrium condition at TJ’s [7]. Relative boundary mobilities were also extracted from TJ’s through a statistical/multiscale analysis [8]. Additionally, there are recent theoretical developments [9] of grain boundary evolution in microstructures. In this paper, a new technique for three-dimensional grain growth simulations was used to simulate interface migration by curvature driven motion [10]. This method utilizes gradientweighted moving finite elements (GWMFE) combined with algorithms for performing topological reconnections on the evolving mesh. We have previously showed a strong similarity between small-scale grain growth experiments and anisotropic three-dimensional simulations [1] obtained from the EBSD measurements [11]. Using the same technique, we obtained 5170-grain data from a thin Aluminum film with a columnar grain structure and compared the computational results with experiments.
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