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
- Philip Bingham
- Ryan Dehoff
- Vincent Paquit
- Christopher Hobbs
- Christopher Rouleau
- Costas Tsouris
- Diana E Hun
- Eddie Lopez Honorato
- Gina Accawi
- Gs Jung
- Gurneesh Jatana
- Gyoung Gug Jang
- Ilia N Ivanov
- Ivan Vlassiouk
- Jong K Keum
- Mark M Root
- Matt Kurley III
- Michael Kirka
- Mina Yoon
- Obaid Rahman
- Philip Boudreaux
- Radu Custelcean
- Rodney D Hunt
- Ryan Heldt
- Tyler Gerczak

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.

Sintering additives to improve densification and microstructure control of UN provides a facile approach to producing high quality nuclear fuels.

This technology is a laser-based heating unit that offers rapid heating profiles on a research scale with minimal incidental heating of materials processing environments.

The use of Fluidized Bed Chemical Vapor Deposition to coat particles or fibers is inherently slow and capital intensive, as it requires constant modifications to the equipment to account for changes in the characteristics of the substrates to be coated.

A novel molecular sorbent system for low energy CO2 regeneration is developed by employing CO2-responsive molecules and salt in aqueous media where a precipitating CO2--salt fractal network is formed, resulting in solid-phase formation and sedimentation.

Simurgh revolutionizes industrial CT imaging with AI, enhancing speed and accuracy in nondestructive testing for complex parts, reducing costs.
Aromas play a significant role in the quality and safety of food, beverages, and even manufactured products. The ability to detect and interpret these aromas accurately can enhance product safety and consumer satisfaction.