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Researcher
- Amit Shyam
- Alex Plotkowski
- James A Haynes
- Peter Wang
- Ryan Dehoff
- Stephen M Killough
- Sumit Bahl
- Adam Stevens
- Alice Perrin
- Andres Marquez Rossy
- Brian Post
- Bruce Moyer
- Bryan Maldonado Puente
- Christopher Fancher
- Corey Cooke
- Dean T Pierce
- Debjani Pal
- Diana E Hun
- Gerry Knapp
- Gordon Robertson
- Jay Reynolds
- Jeff Brookins
- Jeffrey Einkauf
- Jennifer M Pyles
- Jovid Rakhmonov
- Kuntal De
- Laetitia H Delmau
- Luke Sadergaski
- Nicholas Richter
- Nolan Hayes
- Peeyush Nandwana
- Philip Boudreaux
- Rangasayee Kannan
- Roger G Miller
- Ryan Kerekes
- Sally Ghanem
- Sarah Graham
- Sudarsanam Babu
- Sunyong Kwon
- William Peter
- Ying Yang
- Yukinori Yamamoto

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

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.

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.

This invention utilizes new techniques in machine learning to accelerate the training of ML-based communication receivers.

Current technology for heating, ventilation, and air conditioning (HVAC) and other uses such as vending machines rely on refrigerants that have high global warming potential (GWP).