论文标题
使用Minkowski功能对3D原子探针数据进行形态学分析
Morphological analysis of 3d atom probe data using Minkowski functionals
论文作者
论文摘要
我们使用天体物理学群落开发的方法来描述星系的形状。我们使用Minkowski功能来描述第二阶段区域，代表区域的体积，表面积，平均曲率和Euler特征。这项工作中的合金数据显示，可以将微观结构描述为在不同浓度水平下类似海绵状的，类丝状，板状和球形，我们发现这些特征的定量测量值。为了减少构建等曲面的用户决策并提高分析的准确性，开发了最大可能的基于denoising滤波器。我们表明，该过滤器的性能要比简单的高斯平滑过滤器要好得多。我们还使用天然立方花键插入数据，以完善体素大小并改进表面。我们证明，可以找到从原子数据集中的微观结构到无需用户可调参数的数学定义明确的，定量描述到亚素的分辨率。
We present a morphological analysis of atom probe data of nanoscale microstructural features, using methods developed by the astrophysics community to describe the shape of superclusters of galaxies. We describe second-phase regions using Minkowski functionals, representing the regions' volume, surface area, mean curvature and Euler characteristic. The alloy data in this work show microstructures that can be described as sponge-like, filament-like, plate-like, and sphere-like at different concentration levels, and we find quantitative measurements of these features. To reduce user decision-making in constructing isosurfaces and to enhance the accuracy of the analysis a maximum likelihood based denoising filter was developed. We show that this filter performs significantly better than a simple Gaussian smoothing filter. We also interpolate the data using natural cubic splines, to refine voxel sizes and to refine the surface. We demonstrate that it is possible to find a mathematically well-defined, quantitative description of microstructure from atomistic datasets, to sub-voxel resolution, without user-tuneable parameters.
