Identifying chemically similar multiphase nanoprecipitates in compositionally complex non-equilibrium oxides via machine learning

Identifying chemically similar multiphase nanoprecipitates in compositionally complex non-equilibrium oxides via machine learning

Characterizing fission products in uranium dioxide nuclear fuel is important for predicting its long-term properties. Here, machine learning is used to mine microscopy images of precipitates and nanoscale gas bubbles in high-burn-up fuels, providing detailed structural insight of nanoscale fission p...

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Bibliographic Details
Main Authors: Keyou S. Mao, Tyler J. Gerczak, Jason M. Harp, Casey S. McKinney, Timothy G. Lach, Omer Karakoc, Andrew T. Nelson, Kurt A. Terrani, Chad M. Parish, Philip D. Edmondson
Format: Article
Language:English
Published: Nature Portfolio 2022-04-01
Series:Communications Materials
Online Access:https://doi.org/10.1038/s43246-022-00244-4

Internet

https://doi.org/10.1038/s43246-022-00244-4

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