Direct imaging of three-dimensional microstructure via X-ray diffraction-based techniques gives valuable insight into the crystallographic features that influence materials properties and performance. For instance, X-ray diffraction tomography provides information on grain orientation, position, size, and shape in a bulk specimen. As such techniques become more accessible to researchers, demands are placed on processing the datasets that are inherently “noisy,” multi-dimensional, and multimodal. To fulfill this need, we have developed a one-of-a-kind function package, PolyProc, that is compatible with a range of data shapes, from planar sections to time-evolving and three-dimensional orientation data. Our package comprises functions to import, filter, analyze, and visualize the reconstructed grain maps. To accelerate the computations in our pipeline, we harness computationally efficient approaches: for instance, data alignment is done via genetic optimization; grain tracking through the Hungarian method; and feature-to-feature correlation through k-nearest neighbors algorithm. As a proof-of-concept, we test our approach in characterizing the grain texture, topology, and evolution in a polycrystalline Al–Cu alloy undergoing coarsening.

中文翻译：

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PolyProc：用于X射线衍射层析成像的模块化处理管道

通过基于X射线衍射的技术对三维微观结构进行直接成像，可以深入了解影响材料性能和性能的晶体学特征。例如，X射线衍射断层扫描可提供有关大块试样中晶粒取向，位置，大小和形状的信息。随着研究人员更容易使用此类技术，对处理固有“噪点”，多维和多模式的数据集提出了要求。为了满足这一需求，我们开发了一种独一无二的功能包PolyProc，它与各种数据形状兼容，从平面截面到随时间变化的3D方向数据。我们的软件包包括导入，过滤，分析和可视化重建的谷物图的功能。为了加快管道中的计算速度，我们利用了计算有效的方法：例如，通过遗传优化完成数据对齐；通过匈牙利方法进行谷物追踪；和特征到特征的关联k近邻算法。作为概念验证，我们测试了表征粗糙化多晶Al-Cu合金的晶粒织构，拓扑和演变的方法。