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
- Alex Plotkowski
- Amit Shyam
- James A Haynes
- Sumit Bahl
- Alexander I Wiechert
- Alice Perrin
- Andres Marquez Rossy
- Christopher Hobbs
- Costas Tsouris
- Debangshu Mukherjee
- Eddie Lopez Honorato
- Gerry Knapp
- Gs Jung
- Gyoung Gug Jang
- Jovid Rakhmonov
- Matt Kurley III
- Md Inzamam Ul Haque
- Nicholas Richter
- Olga S Ovchinnikova
- Peeyush Nandwana
- Radu Custelcean
- Rodney D Hunt
- Ryan Dehoff
- Ryan Heldt
- Sunyong Kwon
- Tyler Gerczak
- Ying Yang

Currently available cast Al alloys are not suitable for various high-performance conductor applications, such as rotor, inverter, windings, busbar, heat exchangers/sinks, etc.

The invented alloys are a new family of Al-Mg alloys. This new family of Al-based alloys demonstrate an excellent ductility (10 ± 2 % elongation) despite the high content of impurities commonly observed in recycled aluminum.

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.

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

A high-strength, heat-resistant Al-Ce-Ni alloy optimized for additive manufacturing in industrial applications.