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Microstructural characterization of dendritic evolution using two-point statistics
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DOI：10.1016/j.scriptamat.2020.02.034.png)
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Abstract
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Characterizing large four-dimensional materials datasets is difficult due to the presence of complex microstructures and time-varying length scales. We showcase the use of two-point statistics as an efficient and un-biased way of extracting materials parameters from an Al-Cu alloy during solidification. The evolution of dendrite primary arm thickness, average secondary arm spacing, and average tip-to-tip spacing were tracked using two-point Pearson auto-correlations of scaled mean curvatures. Insights into competitive side-branching are also reported. We show both visually and quantitatively that most length scales change rapidly during early stages of dendritic growth, but slow as diffusion fields of dendrites overlap. (C) 2020 Acta Materialia Inc. Published by Elsevier Ltd. All rights reserved.
Keywords:
Dendritic growth
Two-point statistics
Three-dimensional tomography
Solidification microstructure
Aluminum alloys
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