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Researcher
- Amit Shyam
- Alex Plotkowski
- James A Haynes
- Ryan Dehoff
- Sumit Bahl
- Adam Siekmann
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- Andres Marquez Rossy
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- Hong Wang
- Hyeonsup Lim
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- Jovid Rakhmonov
- Mark Provo II
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- Peeyush Nandwana
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- Rangasayee Kannan
- Rob Root
- Roger G Miller
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- Sudarsanam Babu
- Sunyong Kwon
- Vivek Sujan
- William Peter
- Ying Yang
- Yukinori Yamamoto

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 ever-changing cellular communication landscape makes it difficult to identify, map, and localize commercial and private cellular base stations (PCBS).

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.

No readily available public data exists for vehicle class and weight information that covers the entire U.S. highway network. The Travel Monitoring Analysis System, managed by the Federal Highway Administration covers only less than 1% of the US highway network.

Pairing hybrid neural network modeling techniques with artificial intelligence, or AI, controls has resulted in a unique hybrid system that creates a smart solution for traffic-signal timing.

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