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Researcher
- Ying Yang
- Ryan Dehoff
- Singanallur Venkatakrishnan
- Alice Perrin
- Amir K Ziabari
- Diana E Hun
- Michael Kirka
- Philip Bingham
- Philip Boudreaux
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- Steven J Zinkle
- Vincent Paquit
- Yanli Wang
- Yutai Kato
- Alex Plotkowski
- Amit Shyam
- Bruce A Pint
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- Christopher Ledford
- Corey Cooke
- Costas Tsouris
- David S Parker
- Debjani Pal
- Gerry Knapp
- Gina Accawi
- Gs Jung
- Gurneesh Jatana
- Gyoung Gug Jang
- James A Haynes
- Jeffrey Einkauf
- Jennifer M Pyles
- Jong K Keum
- Justin Griswold
- Kuntal De
- Laetitia H Delmau
- Luke Sadergaski
- Mark M Root
- Mike Zach
- Mina Yoon
- Nicholas Richter
- Nolan Hayes
- Obaid Rahman
- Padhraic L Mulligan
- Patxi Fernandez-Zelaia
- Peter Wang
- Radu Custelcean
- Ryan Kerekes
- Sally Ghanem
- Sandra Davern
- Sumit Bahl
- Sunyong Kwon
- Tim Graening Seibert
- Weicheng Zhong
- Wei Tang
- Xiang Chen
- Yan-Ru Lin

ORNL researchers have developed a deep learning-based approach to rapidly perform high-quality reconstructions from sparse X-ray computed tomography measurements.

Ruthenium is recovered from used nuclear fuel in an oxidizing environment by depositing the volatile RuO4 species onto a polymeric substrate.

The invented alloys are a new family of Al-Mg alloys. This new family of Al-based alloys demonstrate an excellent ductility (10 ± 2 % elongation) despite the high content of impurities commonly observed in recycled aluminum.

We have been working to adapt background oriented schlieren (BOS) imaging to directly visualize building leakage, which is fast and easy.

V-Cr-Ti alloys have been proposed as candidate structural materials in fusion reactor blanket concepts with operation temperatures greater than that for reduced activation ferritic martensitic steels (RAFMs).

High strength, oxidation resistant refractory alloys are difficult to fabricate for commercial use in extreme environments.

The first wall and blanket of a fusion energy reactor must maintain structural integrity and performance over long operational periods under neutron irradiation and minimize long-lived radioactive waste.

Spherical powders applied to nuclear targetry for isotope production will allow for enhanced heat transfer properties, tailored thermal conductivity and minimize time required for target fabrication and post processing.

This invention utilizes new techniques in machine learning to accelerate the training of ML-based communication receivers.

Biocompatible nanoparticles have been developed that can trap and retain therapeutic radionuclides and their byproducts at the cancer site. This is important to maximize the therapeutic effect of this treatment and minimize associated side effects.