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Researcher
- Hongbin Sun
- Venkatakrishnan Singanallur Vaidyanathan
- Amir K Ziabari
- Diana E Hun
- Philip Bingham
- Philip Boudreaux
- Prashant Jain
- Ryan Dehoff
- Stephen M Killough
- Vincent Paquit
- Bryan Maldonado Puente
- Corey Cooke
- Dave Willis
- Gina Accawi
- Gurneesh Jatana
- Ian Greenquist
- Ilias Belharouak
- Luke Chapman
- Mark M Root
- Michael Kirka
- Nate See
- Nithin Panicker
- Nolan Hayes
- Obaid Rahman
- Peter Wang
- Pradeep Ramuhalli
- Praveen Cheekatamarla
- Ruhul Amin
- Ryan Kerekes
- Sally Ghanem
- Sydney Murray III
- Thien D. Nguyen
- Vasilis Tzoganis
- Vasiliy Morozov
- Vishaldeep Sharma
- Vittorio Badalassi
- Yun Liu

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 presented a novel apparatus and method for laser beam position detection and pointing stabilization using analog position-sensitive diodes (PSDs).

The invention presented here addresses key challenges associated with counterfeit refrigerants by ensuring safety, maintaining system performance, supporting environmental compliance, and mitigating health and legal 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.

Recent advances in magnetic fusion (tokamak) technology have attracted billions of dollars of investments in startups from venture capitals and corporations to develop devices demonstrating net energy gain in a self-heated burning plasma, such as SPARC (under construction) and

High and ultra-high vacuum applications require seals that do not allow leaks. O-rings can break down over time, due to aging and exposure to radiation. Metallic seals can damage sealing surfaces, making replacement of the original seal very difficult.

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