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Researcher
- Amit Shyam
- Ryan Dehoff
- Alex Plotkowski
- Singanallur Venkatakrishnan
- Amir K Ziabari
- Diana E Hun
- James A Haynes
- Peter Wang
- Philip Bingham
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- Vincent Paquit
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- Andres Marquez Rossy
- Bekki Mills
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- Obaid Rahman
- Peeyush Nandwana
- Rangasayee Kannan
- Roger G Miller
- Ryan Kerekes
- Sally Ghanem
- Sarah Graham
- Shannon M Mahurin
- Sudarsanam Babu
- Sunyong Kwon
- Tao Hong
- Tomonori Saito
- Victor Fanelli
- William Peter
- Ying Yang
- Yukinori Yamamoto

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 lack of real-time insights into how materials evolve during laser powder bed fusion has limited the adoption by inhibiting part qualification. The developed approach provides key data needed to fabricate born qualified parts.

Neutron scattering experiments cover a large temperature range in which experimenters want to test their samples.

Neutron beams are used around the world to study materials for various purposes.