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Researcher
- Ryan Dehoff
- Singanallur Venkatakrishnan
- Vincent Paquit
- Amir K Ziabari
- Michael Kirka
- Philip Bingham
- Adam Stevens
- Ahmed Hassen
- Alex Plotkowski
- Alice Perrin
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- Patxi Fernandez-Zelaia
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- Rangasayee Kannan
- Roger G Miller
- Sarah Graham
- Sudarsanam Babu
- Tony Beard
- Vipin Kumar
- Vlastimil Kunc
- William Peter
- Yan-Ru Lin
- 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.

We have been working to adapt background oriented schlieren (BOS) imaging to directly visualize building leakage, which is fast and easy.

The technologies provide a system and method of needling of veiled AS4 fabric tape.

High strength, oxidation resistant refractory alloys are difficult to fabricate for commercial use in extreme environments.

ORNL will develop an advanced high-performing RTG using a novel radioisotope heat source.

In manufacturing parts for industry using traditional molds and dies, about 70 percent to 80 percent of the time it takes to create a part is a result of a relatively slow cooling process.

This technology combines 3D printing and compression molding to produce high-strength, low-porosity composite articles.

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

An innovative low-cost system for in-situ monitoring of strain and temperature during directed energy deposition.