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Rapid detection of rare events from in situ X-ray diffraction data using machine learning

High-energy X-ray diffraction methods can non-destructively map the 3D microstructure and associated attributes of metallic polycrystalline engineering materials in their bulk form.

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Cite this as

Weijian Zheng, Jun-Sang Park, Peter Kenesei, Ahsan Ali, Zhengchun Liu, Ian T. Foster, Nicholas Schwarz, Rajkumar Kettimuthu, Antonino Miceli, Hemant Sharma (2024). Dataset: Rapid detection of rare events from in situ X-ray diffraction data using machine learning. https://doi.org/10.57702/bb14rr84

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Additional Info

Field	Value
Created	December 16, 2024
Last update	December 16, 2024
Defined In	https://doi.org/10.48550/arXiv.2312.03989
Author	Weijian Zheng
More Authors	Jun-Sang Park Peter Kenesei Ahsan Ali Zhengchun Liu Ian T. Foster Nicholas Schwarz Rajkumar Kettimuthu Antonino Miceli Hemant Sharma
Homepage	https://doi.org/10.1107/S2052252521001258