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Researcher
- Blane Fillingim
- Brian Post
- Lauren Heinrich
- Peeyush Nandwana
- Sudarsanam Babu
- Thomas Feldhausen
- Yousub Lee
- Alexander I Wiechert
- Bruce Moyer
- Callie Goetz
- Christopher Hobbs
- Costas Tsouris
- Debangshu Mukherjee
- Eddie Lopez Honorato
- Fred List III
- Gs Jung
- Gyoung Gug Jang
- Jeffrey Einkauf
- Jennifer M Pyles
- Keith Carver
- Laetitia H Delmau
- Luke Sadergaski
- Matt Kurley III
- Md Inzamam Ul Haque
- Olga S Ovchinnikova
- Radu Custelcean
- Ramanan Sankaran
- Richard Howard
- Rodney D Hunt
- Ryan Heldt
- Thomas Butcher
- Tyler Gerczak
- Vimal Ramanuj
- Wenjun Ge

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

A pressure burst feature has been designed and demonstrated for relieving potentially hazardous excess pressure within irradiation capsules used in the ORNL High Flux Isotope Reactor (HFIR).

Among the methods for point source carbon capture, the absorption of CO2 using aqueous amines (namely MEA) from the post-combustion gas stream is currently considered the most promising.

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

This work seeks to alter the interface condition through thermal history modification, deposition energy density, and interface surface preparation to prevent interface cracking.

Additive manufacturing (AM) enables the incremental buildup of monolithic components with a variety of materials, and material deposition locations.

Ceramic matrix composites are used in several industries, such as aerospace, for lightweight, high quality and high strength materials. But producing them is time consuming and often low quality.

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.

This technology is a strategy for decreasing electromagnetic interference and boosting signal fidelity for low signal-to-noise sensors transmitting over long distances in extreme environments, such as nuclear energy generation applications, particularly for particle detection.

This innovative approach combines optical and spectral imaging data via machine learning to accurately predict cancer labels directly from tissue images.