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Researcher
- Andrzej Nycz
- Chris Masuo
- Amit Shyam
- Peter Wang
- Alex Plotkowski
- Alex Walters
- Peeyush Nandwana
- Blane Fillingim
- Brian Gibson
- Brian Post
- James A Haynes
- Joshua Vaughan
- Lauren Heinrich
- Luke Meyer
- Sudarsanam Babu
- Sumit Bahl
- Thomas Feldhausen
- Udaya C Kalluri
- William Carter
- Yousub Lee
- Akash Jag Prasad
- Alexander I Wiechert
- Alice Perrin
- Andres Marquez Rossy
- Calen Kimmell
- Chelo Chavez
- Christopher Fancher
- Chris Tyler
- Clay Leach
- Costas Tsouris
- Debangshu Mukherjee
- Gerry Knapp
- Gordon Robertson
- Gs Jung
- Gyoung Gug Jang
- J.R. R Matheson
- Jaydeep Karandikar
- Jay Reynolds
- Jeff Brookins
- Jesse Heineman
- John Potter
- Jovid Rakhmonov
- Md Inzamam Ul Haque
- Nicholas Richter
- Olga S Ovchinnikova
- Radu Custelcean
- Ramanan Sankaran
- Riley Wallace
- Ritin Mathews
- Ryan Dehoff
- Sunyong Kwon
- Vimal Ramanuj
- Vincent Paquit
- Vladimir Orlyanchik
- Wenjun Ge
- Xiaohan Yang
- 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.

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.

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.

The lack of real-time insights into how materials evolve during laser powder bed fusion has limited the adoption by inhibiting part qualification. The developed approach provides key data needed to fabricate born qualified parts.

We present the design, assembly and demonstration of functionality for a new custom integrated robotics-based automated soil sampling technology as part of a larger vision for future edge computing- and AI- enabled bioenergy field monitoring and management technologies called

Creating a framework (method) for bots (agents) to autonomously, in real time, dynamically divide and execute a complex manufacturing (or any suitable) task in a collaborative, parallel-sequential way without required human interaction.

Materials produced via additive manufacturing, or 3D printing, can experience significant residual stress, distortion and cracking, negatively impacting the manufacturing process.

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.