Open and strong‐scaling tools for atom‐probe crystallography: high‐throughput methods for indexing crystal structure and orientation. Issue 5 (1st October 2021)

• Record Type: Journal Article
• Authors: Kühbach, Markus; Kasemer, Matthew; Gault, Baptiste; Breen, Andrew
• Is Part Of: Journal of applied crystallography. Volume 54:Issue 5(2021)
• Page Start: 1490
• Page End: 1508
• Publication Date: 2021-10-01
• Subjects: crystal structure identification -- atom‐probe tomography -- orientation mapping -- point cloud data -- parallelization; Crystallography -- Periodicals; 548.05
• DOI: 10.1107/S1600576721008578
• Languages: English
• ISSNs: 0021-8898

Abstract

Abstract : It is now recognized that, beyond composition mapping in three dimensions, atom‐probe tomography can provide partial crystallographic information for the material volume under investigation. Detailed here is an original solution for identifying the crystal structure and crystal orientations within atom‐probe tomographic reconstructions. The reported tools are open‐source software and scale strongly on at least 3200 computing cores or 160 graphics cards. Abstract : Volumetric crystal structure indexing and orientation mapping are key data processing steps for virtually any quantitative study of spatial correlations between the local chemical composition features and the microstructure of a material. For electron and X‐ray diffraction methods it is possible to develop indexing tools which compare measured and analytically computed patterns to decode the structure and relative orientation within local regions of interest. Consequently, a number of numerically efficient and automated software tools exist to solve the above characterization tasks. For atom‐probe tomography (APT) experiments, however, the strategy of making comparisons between measured and analytically computed patterns is less robust because many APT data sets contain substantial noise. Given that sufficiently general predictive models for such noise remain elusive, crystallography tools for APT face several limitations: their robustness to noise is limited, and therefore so too is their capability to identify and distinguish different crystal structures and orientations. In addition, the tools are sequential and demand substantial manual interaction. In combination, this makes robust uncertainty quantification with automated high‐throughput studies of the latent crystallographic information a difficult task with APT data. To improve the situation, the existing methods are reviewed and how they link to the methods currently used by the electron and X‐ray diffraction communities is discussed. As a result of this, some of the APT methods are modified to yield more robust descriptors of the atomic arrangement. Also reported is how this enables the development of an open‐source software tool for strong scaling and automated identification of a crystal structure, and the mapping of crystal orientation in nanocrystalline APT data sets with multiple phases.