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Researcher
- Vivek Sujan
- Amit Shyam
- Beth L Armstrong
- Peeyush Nandwana
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- Jun Qu
- Omer Onar
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- Chad Steed
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- Ethan Self
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- Govindarajan Muralidharan
- Harper Jordan
- Hyeonsup Lim
- Isaac Sikkema
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- Jeff Brookins
- Jian Chen
- Jiheon Jun
- Joel Asiamah
- Joel Dawson
- Jordan Wright
- Joseph Olatt
- Jovid Rakhmonov
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- Khryslyn G Araño
- Kunal Mondal
- Lilian V Swann
- Luke Koch
- Mahim Mathur
- Mark Provo II
- Marm Dixit
- Mary A Adkisson
- Matthew S Chambers
- Michael Kirka
- Nance Ericson
- Nancy Dudney
- Nicholas Richter
- Oscar Martinez
- Peter Wang
- Priyanshi Agrawal
- Raymond Borges Hink
- Rob Root
- Roger G Miller
- Rose Montgomery
- Samudra Dasgupta
- Sarah Graham
- Sergiy Kalnaus
- Srikanth Yoginath
- Steven J Zinkle
- Sunyong Kwon
- Thomas R Muth
- Tim Graening Seibert
- T Oesch
- Tolga Aytug
- Trevor Aguirre
- Varisara Tansakul
- Venugopal K Varma
- Weicheng Zhong
- Wei Tang
- Wei Zhang
- William Peter
- Xiang Chen
- Yanli Wang
- Yarom Polsky
- Yiyu Wang
- Yukinori Yamamoto
- Yutai Kato

A finite element approach integrated with a novel constitute model to predict phase change, residual stresses and part deformation.

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 growing demand for electric vehicles (EVs) has necessitated significant advancements in EV charging technologies to ensure efficient and reliable operation.

The growing demand for renewable energy sources has propelled the development of advanced power conversion systems, particularly in applications involving fuel cells.

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.

A new nanostructured bainitic steel with accelerated kinetics for bainite formation at 200 C was designed using a coupled CALPHAD, machine learning, and data mining approach.