Full length article Examination of computed aluminum grain boundary structures and energies that span the 5D space of crystallographic character

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 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 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.(c) 2022 Acta Materialia Inc. Published by Elsevier Ltd. All rights reserved.

Automated summary

This study presents a computed dataset of 7304 unique aluminum grain boundaries in the 5D crystallographic space. The dataset includes a range of atomic configurations for each structure and has great potential for understanding the relationship between grain boundary structure and properties.