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Researcher
- Venkatakrishnan Singanallur Vaidyanathan
- Amir K Ziabari
- Diana E Hun
- Philip Bingham
- Philip Boudreaux
- Rob Moore II
- Ryan Dehoff
- Stephen M Killough
- Vincent Paquit
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- Gurneesh Jatana
- Hongbin Sun
- Mark M Root
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- Michael Kirka
- Nate See
- Nolan Hayes
- Obaid Rahman
- Peter Wang
- Prashant Jain
- Ryan Kerekes
- Sally Ghanem
- Thien D. Nguyen

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

In nuclear and industrial facilities, fine particles, including radioactive residues—can accumulate on the interior surfaces of ventilation ducts and equipment, posing serious safety and operational risks.

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.

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

Molecular Beam Epitaxy is a traditional technique for the synthesis of thin film materials used in the semiconducting and microelectronics industry. In its essence, the MBE technique heats crucibles filled with ultra-pure atomic elements under ultra high vacuum condition

Current technology for heating, ventilation, and air conditioning (HVAC) and other uses such as vending machines rely on refrigerants that have high global warming potential (GWP).

Technologies for optimizing prefab retrofit panel installation using a real-time evaluator is described.