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Douglas L. Porter

Government of the United States of America - Idaho National Laboratory

Box 1625

Idaho Falls, ID 83415

United States

  • Government of the United States of America - Idaho National Laboratory

SCHOLARLY PAPERS

2

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154

TOTAL CITATIONS

1

Scholarly Papers (2)

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1.

An Integrated Approach to Examining Fuel-Cladding Chemical Interaction in Ht9/U-10zr Metallic Fast Reactor Fuels: Coupling Machine Learning with Electron Microscopy and Local Mechanical Properties Analysis

Number of pages: 50 Posted: 13 Feb 2025
Yachun Wang, Luca Capriotti, Fidelma Di Lemma, Daniele Salvato, Fei Xu, Yalei Tang, Kyle M. Paaren, Alexander L. Swearingen and Douglas L. Porter
Government of the United States of America - Idaho National Laboratory, Government of the United States of America - Idaho National Laboratory, Government of the United States of America - Idaho National Laboratory, Government of the United States of America - Idaho National Laboratory, Government of the United States of America - Idaho National Laboratory, Government of the United States of America - Idaho National Laboratory, Government of the United States of America - Idaho National Laboratory, Government of the United States of America - Idaho National Laboratory and Government of the United States of America - Idaho National Laboratory
Downloads 108 (649,907)
Citation 1

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Metallic fuel, HT9/U-10Zr fuel, Fuel-cladding chemical interaction (FCCI), Scanning electron microscopy (SEM), Energy dispersive x-rays spectroscopy (EDS), Machine learning (ML)

2.

Quantification of Line Dislocations in Fftf Irradiated Ht9 Cladding by Deep Learning Method

Number of pages: 10 Posted: 27 Feb 2025
Liang Zhao, Fei Xu, Douglas L. Porter and Yachun Wang
Government of the United States of America - Idaho National Laboratory, Government of the United States of America - Idaho National Laboratory, Government of the United States of America - Idaho National Laboratory and Government of the United States of America - Idaho National Laboratory
Downloads 46 (1,109,210)

Abstract:

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dislocations, (Scanning) transmission electron Microscopy: Edge detection, End-to-end, Deep learning (DL)