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Researcher
- Ryan Dehoff
- Alex Plotkowski
- Amit Shyam
- Vincent Paquit
- Alice Perrin
- James A Haynes
- Michael Kirka
- Sumit Bahl
- Ying Yang
- Adam Stevens
- Ahmed Hassen
- Akash Jag Prasad
- Amir K Ziabari
- Andres Marquez Rossy
- Blane Fillingim
- Brian Post
- Calen Kimmell
- Canhai Lai
- Christopher Ledford
- Chris Tyler
- Clay Leach
- Costas Tsouris
- David Nuttall
- Gerry Knapp
- James Haley
- James Parks II
- Jaydeep Karandikar
- Jovid Rakhmonov
- Nicholas Richter
- Patxi Fernandez-Zelaia
- Peeyush Nandwana
- Philip Bingham
- Rangasayee Kannan
- Roger G Miller
- Sarah Graham
- Singanallur Venkatakrishnan
- Sudarsanam Babu
- Sunyong Kwon
- Vipin Kumar
- Vladimir Orlyanchik
- Vlastimil Kunc
- William Peter
- Yan-Ru Lin
- Yukinori Yamamoto
- Zackary Snow

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.

System and method for part porosity monitoring of additively manufactured components using machining
In additive manufacturing, choice of process parameters for a given material and geometry can result in porosities in the build volume, which can result in scrap.

Sensing of additive manufacturing processes promises to facilitate detailed quality inspection at scales that have seldom been seen in traditional manufacturing processes.

High strength, oxidation resistant refractory alloys are difficult to fabricate for commercial use in extreme environments.

In manufacturing parts for industry using traditional molds and dies, about 70 percent to 80 percent of the time it takes to create a part is a result of a relatively slow cooling process.

This technology combines 3D printing and compression molding to produce high-strength, low-porosity composite articles.

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

An innovative low-cost system for in-situ monitoring of strain and temperature during directed energy deposition.