对跨越晶体学特征5维空间的计算铝晶界结构与界面能的研究
Examination of computed aluminum grain boundary structures and interface energies that span the 5D space of crystallographic character
AI总结：
本研究构建了包含7304余种独特铝晶界、超4300万种结构的5维晶体学空间计算数据集，分析了能量趋势与构效关系，为晶界研究提供了有价值的公开数据资源。
摘要：
可能的晶界结构空间极为广阔，存在5个定义晶界特征的宏观晶体学自由度。尽管已有众多晶界数据集对该空间进行了部分或全部探究，我们仍提出了一个计算得到的数据集，涵盖5维晶体学空间中超过7304种独特的铝晶界。我们的采样还包含了每种独特5维晶体结构对应的一系列可能的微观原子构型，总结构数超过4300万。本文概述了生成该数据集所用的方法，初步考察了遵循Read-Shockley关系的能量趋势，揭示了整个5维空间中的趋势线索、考察非最低能量结构时的晶界（GB）能量变化，以及在机器学习晶界能量构效关系中获得的洞见。该数据集可供下载，在揭示晶界构效关系方面具有巨大潜力。
英文摘要：
The space of possible grain boundary structures is vast, with 5 macroscopic, crystallographic degrees of freedom that define the character of a grain boundary. While numerous datasets of grain boundaries have examined this space in part or in full, we present a computed dataset of over 7304 unique aluminum grain boundaries in the 5D crystallographic space. Our sampling also includes a range of possible microscopic, atomic configurations for each unique 5D crystallographic structure, which total over 43 million structures. We present an overview of the methods used to generate this dataset, an initial examination of the energy trends that follow the Read-Shockley relationship, hints at trends throughout the 5D space, variations in GB energy when non-minimum energy structures are examined, and insights gained in machine learning of grain boundary energy structure-property relationships. This dataset, which is available for download, has great potential for insight into GB structure-property relationships.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
