Abstract 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.

中文翻译：

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使用两点统计对树突演化的微观结构表征

摘要 由于存在复杂的微观结构和随时间变化的长度尺度，表征大型四维材料数据集很困难。我们展示了使用两点统计作为在凝固过程中从 Al-Cu 合金中提取材料参数的一种有效且无偏的方法。使用缩放平均曲率的两点皮尔逊自相关跟踪枝晶初级臂厚度、平均次级臂间距和平均尖端到尖端间距的演变。还报告了对竞争侧分支的见解。我们从视觉上和定量上都表明，在树突生长的早期阶段，大多数长度尺度变化迅速，但随着树突的扩散场重叠而变化缓慢。