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Researcher
- Alex Plotkowski
- Amit Shyam
- Ryan Dehoff
- Singanallur Venkatakrishnan
- Amir K Ziabari
- Diana E Hun
- James A Haynes
- Philip Bingham
- Philip Boudreaux
- Stephen M Killough
- Sumit Bahl
- Vincent Paquit
- Alice Perrin
- Andres Marquez Rossy
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- Ben Garrison
- Brad Johnson
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- Charlie Cook
- Christopher Hershey
- Corey Cooke
- Craig Blue
- Daniel Rasmussen
- Gerry Knapp
- Gina Accawi
- Gurneesh Jatana
- Hsin Wang
- James Klett
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- Jovid Rakhmonov
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- Michael Kirka
- Mike Zach
- Nedim Cinbiz
- Nicholas Richter
- Nolan Hayes
- Obaid Rahman
- Peeyush Nandwana
- Peter Wang
- Ryan Kerekes
- Sally Ghanem
- Sunyong Kwon
- Tony Beard
- Ying Yang

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

Currently available cast Al alloys are not suitable for various high-performance conductor applications, such as rotor, inverter, windings, busbar, heat exchangers/sinks, etc.

The invented alloys are a new family of Al-Mg alloys. This new family of Al-based alloys demonstrate an excellent ductility (10 ± 2 % elongation) despite the high content of impurities commonly observed in recycled aluminum.

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

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

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

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

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.