论文标题
Favad：用于表征和可视化晶体中缺陷的软件工作流程
FaVAD: A software workflow for characterisation and visualizing of defects in crystalline structures
论文作者
论文摘要
晶体材料中缺陷和缺陷动态的分析对于基本科学和广泛的应用工程非常重要。随着系统大小的增加，分子动力学模拟数据的分析变得非平凡。在这里，我们提出了一个工作流，用于对晶体结构中缺陷的半自动识别和分类，将缺陷描述的新方法与几个已经存在的开源软件包结合在一起。我们的方法解决了样品的修改部分，热运动以及辐射后潜在不可预见的原子构型（缺陷类型）的通常相对较小的体积分数所带来的关键挑战。任何原子的局部环境都转化为旋转不变的描述矢量（“指纹”），可以将其与已知的缺陷类型进行比较，还产生适合分类的距离度量。无法与已知结构相关的向量表示新型缺陷类型。作为概念验证，我们将方法应用于铁样品，以分析由10 keV原子敲击引起的碰撞级联反应引起的缺陷。所获得的结果与报告的文献价值非常吻合。
The analysis of defects and defect dynamics in crystalline materials is important for fundamental science and for a wide range of applied engineering. With increasing system size the analysis of molecular-dynamics simulation data becomes non-trivial. Here, we present a workflow for semi-automatic identification and classification of defects in crystalline structures, combining a new approach for defect description with several already existing open-source software packages. Our approach addresses the key challenges posed by the often relatively tiny volume fraction of the modified parts of the sample, thermal motion and the presence of potentially unforeseen atomic configurations (defect types) after irradiation. The local environment of any atom is converted into a rotation-invariant descriptive vector ('fingerprint'), which can be compared to known defect types and also yields a distance metric suited for classification. Vectors which cannot be associated to known structures indicate new types of defects. As proof-of-concept we apply our method on an iron sample to analyze the defects caused by a collision cascade induced by a 10 keV primary-knock-on-atom. The obtained results are in good agreement with reported literature values.
