Filter Results
Related Organization
- Biological and Environmental Systems Science Directorate (23)
- Computing and Computational Sciences Directorate (35)
- Energy Science and Technology Directorate
(217)
- Fusion and Fission Energy and Science Directorate (21)
- Information Technology Services Directorate (2)
- Isotope Science and Enrichment Directorate (6)
- National Security Sciences Directorate (17)
- Neutron Sciences Directorate (11)
- Physical Sciences Directorate
(128)
- User Facilities (27)
Researcher
- Singanallur Venkatakrishnan
- Adam Willoughby
- Amir K Ziabari
- Philip Bingham
- Rishi Pillai
- Ryan Dehoff
- Vincent Paquit
- Brandon Johnston
- Bruce A Pint
- Charles Hawkins
- Diana E Hun
- Gerald Tuskan
- Gina Accawi
- Gurneesh Jatana
- Ilenne Del Valle Kessra
- Jiheon Jun
- Marie Romedenne
- Mark M Root
- Michael Kirka
- Obaid Rahman
- Paul Abraham
- Philip Boudreaux
- Priyanshi Agrawal
- Xiaohan Yang
- Yang Liu
- 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).

Detection of gene expression in plants is critical for understanding the molecular basis of plant physiology and plant responses to drought, stress, climate change, microbes, insects and other factors.

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.