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Researcher
- Venkatakrishnan Singanallur Vaidyanathan
- Adam Willoughby
- Amir K Ziabari
- Philip Bingham
- Rishi Pillai
- Ryan Dehoff
- Vincent Paquit
- Brandon Johnston
- Bruce A Pint
- Charles Hawkins
- Diana E Hun
- Femi Omitaomu
- Gina Accawi
- Gurneesh Jatana
- Haowen Xu
- Jiheon Jun
- Marie Romedenne
- Mark M Root
- Michael Kirka
- Obaid Rahman
- Philip Boudreaux
- Priyanshi Agrawal
- Yong Chae Lim
- 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 novel method that prevents detachment of an optical fiber from a metal/alloy tube and allows strain measurement up to higher temperatures, about 800 C has been developed. Standard commercial adhesives typically only survive up to about 400 C.

Test facilities to evaluate materials compatibility in hydrogen are abundant for high pressure and low temperature (<100C).

We will develop an AI-powered autonomous software development pipeline to help urban scientists develop advanced research software (e.g., digital twins and cyberinfrastructure) to support smart city research and management without the need to write codes or know software engin

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.

The technology provides a transformational approach to digitally manufacture structural alloys with co- optimized strength and environmental resistance

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