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Researcher
- Michael Kirka
- Ryan Dehoff
- Rangasayee Kannan
- Singanallur Venkatakrishnan
- Adam Stevens
- Amir K Ziabari
- Christopher Ledford
- Peeyush Nandwana
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- Vincent Paquit
- Alice Perrin
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- Brian Post
- Corson Cramer
- Diana E Hun
- Fred List III
- Gina Accawi
- Gurneesh Jatana
- James Klett
- Keith Carver
- Mark M Root
- Nate See
- Obaid Rahman
- Patxi Fernandez-Zelaia
- Philip Boudreaux
- Prashant Jain
- Richard Howard
- Roger G Miller
- Sarah Graham
- Steve Bullock
- Sudarsanam Babu
- Thomas Butcher
- Trevor Aguirre
- William Peter
- Yan-Ru Lin
- Ying Yang
- Yukinori Yamamoto

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

A pressure burst feature has been designed and demonstrated for relieving potentially hazardous excess pressure within irradiation capsules used in the ORNL High Flux Isotope Reactor (HFIR).

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

A novel approach is presented herein to improve time to onset of natural convection stemming from fuel element porosity during a failure mode of a nuclear reactor.
Red mud residue is an industrial waste product generated during the processing of bauxite ore to extract alumina for the steelmaking industry. Red mud is rich in minerals in bauxite like iron and aluminum oxide, but also heavy metals, including arsenic and mercury.

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

This technology aims to provide and integrated and oxidation resistant cladding or coating onto carbon-based composites in seconds.