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Researcher
- Venkatakrishnan Singanallur Vaidyanathan
- Amir K Ziabari
- Andrzej Nycz
- Chris Masuo
- Luke Meyer
- Mike Zach
- Philip Bingham
- Ryan Dehoff
- Vincent Paquit
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- Craig Blue
- Daniel Rasmussen
- Debjani Pal
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- Gurneesh Jatana
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- Kevin Sparks
- Kuntal De
- Laetitia H Delmau
- Liz McBride
- Loren L Funk
- Luke Sadergaski
- Mark M Root
- Michael Kirka
- Nedim Cinbiz
- Obaid Rahman
- Padhraic L Mulligan
- Peter Wang
- Philip Boudreaux
- Polad Shikhaliev
- Sandra Davern
- Theodore Visscher
- Todd Thomas
- Tony Beard
- Vladislav N Sedov
- Xiuling Nie
- Yacouba Diawara

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

Often there are major challenges in developing diverse and complex human mobility metrics systematically and quickly.

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

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

ORNL has developed a large area thermal neutron detector based on 6LiF/ZnS(Ag) scintillator coupled with wavelength shifting fibers. The detector uses resistive charge divider-based position encoding.

The technologies provide a system and method of needling of veiled AS4 fabric tape.

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.

ORNL will develop an advanced high-performing RTG using a novel radioisotope heat source.