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

Author

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, and Philip D. Edmondson

Subjects
Materials of engineering and construction. Mechanics of materials, TA401-492
Abstract

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 products.

Published
2022
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