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CONNECTIVITY IN RANDOM GRAIN BOUNDARY NETWORKS

机译:随机晶界网络中的连接

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Mechanical properties of FCC metals and alloys can be improved by exercising control over the population of grain boundary types in the microstructure. The existing studies also suggest that such properties tend to have percolative mechanisms that depend on the topology of the grain boundary network. With the emergence of SEM-based automated electron backscatter diffraction (EBSD), statistically significant datasets of interface crystallography can be analyzed in a routine manner, giving new insight into the topology and percolative properties of grain boundary networks. In this work, we review advanced analysis techniques for EBSD datasets to quantify microstructures in terms of grain boundary character and triple junction distributions, as well as detailed percolation-theory based cluster analysis.
机译:通过对微观结构中的晶粒边界类型的群体进行控制,可以改善FCC金属和合金的机械性能。现有研究还表明,这些性质倾向于具有渗透机制,这取决于晶界网络的拓扑。随着SEM的自动电子反向散射衍射(EBSD)的出现,可以以常规方式分析静态晶体学的统计学显着的数据集,以常规方式分析晶粒边界网络的拓扑和渗透性质的新洞察。在这项工作中,我们审查了EBSD数据集的高级分析技术,以在晶界特征和三界分布方面进行量化的微观结构,以及基于细化的基于渗透理论的聚类分析。

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