What is it about?
It introduces a machine learning approach to analyze complex X-ray Laue patterns on the fly.
Photo by Markus Spiske on Unsplash
Why is it important?
Grain morphology, textures and crystal structures are the most important structure factors, which directly determine the properties of solid materials. By state-of-art synchrotron X-ray microdiffraction, all these three characteristics can be measured simultaneously. However, the analysis of tens of thousands of Laue patterns is quite time consuming, sometime is impossible for unknown crystals. We developed a machine learning approach that can generate an orientation map from a set of Laue scans without knowing the crystal structure and indexing information.
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This page is a summary of: Data-driven approach for synchrotron X-ray Laue microdiffraction scan analysis, Acta Crystallographica Section A Foundations and Advances, October 2019, International Union of Crystallography, DOI: 10.1107/s2053273319012804.
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