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Researcher
- Ryan Dehoff
- Singanallur Venkatakrishnan
- Yong Chae Lim
- Amir K Ziabari
- Philip Bingham
- Rangasayee Kannan
- Vincent Paquit
- Adam Stevens
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- Gurneesh Jatana
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- Sudarsanam Babu
- Thomas Butcher
- Tomas Grejtak
- 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.

A pressure burst feature has been designed and demonstrated for relieving potentially hazardous excess pressure within irradiation capsules used in the ORNL High Flux Isotope Reactor (HFIR).

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.

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.

Simurgh revolutionizes industrial CT imaging with AI, enhancing speed and accuracy in nondestructive testing for complex parts, reducing costs.