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
- Amir K Ziabari
- Mingyan Li
- Philip Bingham
- Ryan Dehoff
- Sam Hollifield
- Vincent Paquit
- Brian Weber
- Diana E Hun
- Gina Accawi
- Gurneesh Jatana
- Huixin (anna) Jiang
- Isaac Sikkema
- Jamieson Brechtl
- Joseph Olatt
- Kai Li
- Kashif Nawaz
- Kevin Spakes
- Kunal Mondal
- Lilian V Swann
- Luke Koch
- Mahim Mathur
- Mark M Root
- Mary A Adkisson
- Michael Kirka
- Obaid Rahman
- Oscar Martinez
- Philip Boudreaux
- T Oesch
- Xiaobing Liu

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.

Moisture management accounts for over 40% of the energy used by buildings. As such development of energy efficient and resilient dehumidification technologies are critical to decarbonize the building energy sector.

Real-time tracking and monitoring of radioactive/nuclear materials during transportation is a critical need to ensure safety and security. Current technologies rely on simple tagging, using sensors attached to transport containers, but they have limitations.

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