Work

Density-based clustering of crystal orientations and misorientations and the orix python library

Year: 2020

Type: preprint

Abstract: Crystal orientation mapping experiments typically measure orientations that are similar within grains and misorientations that are similar along grain boundaries. Such (mis)orientation data will cluster in (mis)orientation space and clusters are more pronounced if preferred orientations or special orientation relationships are present. Here, cluster analysis of (mis)orientation data is described and demonstrated using distance metrics incorporating crystal symmetry and the density-based clustering algorithm DBSCAN. Frequently measured (mis)orientations are identified as corresponding to grains, grain boundaries or orientation relationships, which are visualised both spatially and in three-dimensional (mis)orientation spaces. A new open-source python library, orix, is also reported.

Source: arXiv (Cornell University)

DOI: 10.48550/arxiv.2001.02716

Authors: Johnstone, Duncan N., Martineau, Ben H., Crout, Phillip, Midgley, Paul A., Eggeman, Alexander S.

Institutions: University of Cambridge, University of Manchester

Language: English

Topic: Microstructure and mechanical properties

Subfield: Materials Chemistry

Field: Materials Science

Domain: Physical Sciences

Open Access status: green

Funders: Royal Society, Engineering and Physical Sciences Research Council, National Physical Laboratory

Awards: Electron Diffraction Based Nano-Metrology, G3209211212, G4509676128, G4870660297, Multi-Dimensional Electron Microscope

OpenAlex ID: W2999111587

Cites: 7

Cited by: 1

Related to: 20