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Researcher
- Ryan Dehoff
- Singanallur Venkatakrishnan
- Vincent Paquit
- Amir K Ziabari
- Diana E Hun
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- Stephen M Killough
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- Andres Marquez Rossy
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- Vasilis Tzoganis
- Vasiliy Morozov
- Vipin Kumar
- Vlastimil Kunc
- William Peter
- Yan-Ru Lin
- Ying Yang
- Yukinori Yamamoto
- Yun Liu

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

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

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

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

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.

In manufacturing parts for industry using traditional molds and dies, about 70 percent to 80 percent of the time it takes to create a part is a result of a relatively slow cooling process.

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).

The technology describes an electron beam in a storage ring as a quantum computer.