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Researcher
- Ryan Dehoff
- Alex Plotkowski
- Amit Shyam
- Singanallur Venkatakrishnan
- Yong Chae Lim
- Amir K Ziabari
- Diana E Hun
- James A Haynes
- Peeyush Nandwana
- Philip Bingham
- Philip Boudreaux
- Rangasayee Kannan
- Stephen M Killough
- Sumit Bahl
- Vincent Paquit
- Adam Stevens
- Alice Perrin
- Andres Marquez Rossy
- Brian Post
- Bryan Lim
- Bryan Maldonado Puente
- Corey Cooke
- Gerry Knapp
- Gina Accawi
- Gurneesh Jatana
- Jiheon Jun
- Jovid Rakhmonov
- Mark M Root
- Michael Kirka
- Nicholas Richter
- Nolan Hayes
- Obaid Rahman
- Peter Wang
- Priyanshi Agrawal
- Roger G Miller
- Ryan Kerekes
- Sally Ghanem
- Sarah Graham
- Sudarsanam Babu
- Sunyong Kwon
- Tomas Grejtak
- William Peter
- Ying Yang
- Yiyu Wang
- Yukinori Yamamoto
- Zhili Feng

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.

A new nanostructured bainitic steel with accelerated kinetics for bainite formation at 200 C was designed using a coupled CALPHAD, machine learning, and data mining approach.

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

The technologies provide a coating method to produce corrosion resistant and electrically conductive coating layer on metallic bipolar plates for hydrogen fuel cell and hydrogen electrolyzer applications.

Welding high temperature and/or high strength materials for aerospace or automobile manufacturing is challenging.