Processing Laue Microdiffraction Raster Scanning Patterns with Machine Learning Algorithms: A Case Study with a Fatigued Polycrystalline Sample

Processing Laue Microdiffraction Raster Scanning Patterns with Machine Learning Algorithms: A Case Study with a Fatigued Polycrystalline Sample

The massive amount of diffraction images collected in a raster scan of Laue microdiffraction calls for a fast treatment with little if any human intervention. The conventional method that has to index diffraction patterns one-by-one is laborious and can hardly give real-time feedback. In this work,...

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Bibliographic Details
Main Authors: Peng Rong, Fengguo Zhang, Qing Yang, Han Chen, Qiwei Shi, Shengyi Zhong, Zhe Chen, Haowei Wang
Format: Article
Language:English
Published: MDPI AG 2022-02-01
Series:Materials
Subjects:
Laue microdiffraction
unsupervised machine learning
fatigued microstructure
Online Access:https://www.mdpi.com/1996-1944/15/4/1502

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https://www.mdpi.com/1996-1944/15/4/1502

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