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Researcher
- Alex Plotkowski
- Amit Shyam
- Peeyush Nandwana
- Ryan Dehoff
- Singanallur Venkatakrishnan
- Amir K Ziabari
- Blane Fillingim
- Brian Post
- Diana E Hun
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- Philip Boudreaux
- Stephen M Killough
- Sudarsanam Babu
- Sumit Bahl
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- Vincent Paquit
- Yousub Lee
- Alice Perrin
- Andres Marquez Rossy
- Bryan Maldonado Puente
- Corey Cooke
- Gerry Knapp
- Gina Accawi
- Gurneesh Jatana
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- Mark M Root
- Michael Kirka
- Nicholas Richter
- Nolan Hayes
- Obaid Rahman
- Peter Wang
- Ramanan Sankaran
- Ryan Kerekes
- Sally Ghanem
- Sunyong Kwon
- Vimal Ramanuj
- Wenjun Ge
- 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.

This work seeks to alter the interface condition through thermal history modification, deposition energy density, and interface surface preparation to prevent interface cracking.

Additive manufacturing (AM) enables the incremental buildup of monolithic components with a variety of materials, and material deposition locations.

Ceramic matrix composites are used in several industries, such as aerospace, for lightweight, high quality and high strength materials. But producing them is time consuming and often low quality.

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).