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
- Ryan Dehoff
- Singanallur Venkatakrishnan
- Yong Chae Lim
- Amir K Ziabari
- Philip Bingham
- Rangasayee Kannan
- Vincent Paquit
- Adam Stevens
- An-Ping Li
- Brian Post
- Bryan Lim
- Diana E Hun
- Gina Accawi
- Gurneesh Jatana
- Hoyeon Jeon
- Jewook Park
- Jiheon Jun
- Mark M Root
- Michael Kirka
- Obaid Rahman
- Peeyush Nandwana
- Philip Boudreaux
- Priyanshi Agrawal
- Roger G Miller
- Saban Hus
- Sarah Graham
- Sudarsanam Babu
- 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.

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.

Distortion in scanning tunneling microscope (STM) images is an unavoidable problem. This technology is an algorithm to identify and correct distorted wavefronts in atomic resolution STM images.

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.