Filter Results
Related Organization
- Biological and Environmental Systems Science Directorate (29)
- Computing and Computational Sciences Directorate (39)
- Energy Science and Technology Directorate
(229)
- Fusion and Fission Energy and Science Directorate
(24)
- Information Technology Services Directorate (3)
- National Security Sciences Directorate (20)
- Neutron Sciences Directorate (11)
- Physical Sciences Directorate (138)
- User Facilities (28)
- (-) Isotope Science and Enrichment Directorate (7)
Researcher
- Venkatakrishnan Singanallur Vaidyanathan
- Amir K Ziabari
- Diana E Hun
- Mike Zach
- Philip Bingham
- Philip Boudreaux
- Ryan Dehoff
- Stephen M Killough
- Vincent Paquit
- Andrew F May
- Annetta Burger
- Ben Garrison
- Brad Johnson
- Bruce Moyer
- Bryan Maldonado Puente
- Carter Christopher
- Chance C Brown
- Charlie Cook
- Christopher Hershey
- Corey Cooke
- Craig Blue
- Daniel Rasmussen
- Debjani Pal
- Debraj De
- Gautam Malviya Thakur
- Gina Accawi
- Gurneesh Jatana
- Hsin Wang
- James Gaboardi
- James Klett
- Jeffrey Einkauf
- Jennifer M Pyles
- Jesse McGaha
- John Holliman II
- John Lindahl
- Justin Griswold
- Kevin Sparks
- Kuntal De
- Laetitia H Delmau
- Liz McBride
- Luke Sadergaski
- Mark M Root
- Michael Kirka
- Nedim Cinbiz
- Nithin Panicker
- Nolan Hayes
- Obaid Rahman
- Padhraic L Mulligan
- Peter Wang
- Prashant Jain
- Ryan Kerekes
- Sally Ghanem
- Sandra Davern
- Todd Thomas
- Tony Beard
- Vittorio Badalassi
- Xiuling Nie

ORNL researchers have developed a deep learning-based approach to rapidly perform high-quality reconstructions from sparse X-ray computed tomography measurements.

How fast is a vehicle traveling? For different reasons, this basic question is of interest to other motorists, insurance companies, law enforcement, traffic planners, and security personnel. Solutions to this measurement problem suffer from a number of constraints.

Often there are major challenges in developing diverse and complex human mobility metrics systematically and quickly.

Ruthenium is recovered from used nuclear fuel in an oxidizing environment by depositing the volatile RuO4 species onto a polymeric substrate.

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.

Recent advances in magnetic fusion (tokamak) technology have attracted billions of dollars of investments in startups from venture capitals and corporations to develop devices demonstrating net energy gain in a self-heated burning plasma, such as SPARC (under construction) and

Spherical powders applied to nuclear targetry for isotope production will allow for enhanced heat transfer properties, tailored thermal conductivity and minimize time required for target fabrication and post processing.

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