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Researcher
- Ryan Dehoff
- Singanallur Venkatakrishnan
- Yong Chae Lim
- Amir K Ziabari
- Diana E Hun
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- Rangasayee Kannan
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- Sally Ghanem
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- Sudarsanam Babu
- Tomas Grejtak
- Vittorio Badalassi
- William Peter
- 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.

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.

Recent advances in magnetic fusion (tokamak) technology have attracted billions of dollars of investments in startups from venture capitals and corporations to develop devices demonstrating net energy gain in a self-heated burning plasma, such as SPARC (under construction) and

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.