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Researcher
- Peeyush Nandwana
- Ying Yang
- Amit Shyam
- Brian Post
- Rangasayee Kannan
- Ryan Dehoff
- Sudarsanam Babu
- Yong Chae Lim
- Zhili Feng
- Alex Plotkowski
- Alice Perrin
- Blane Fillingim
- Jian Chen
- Lauren Heinrich
- Steven J Zinkle
- Thomas Feldhausen
- Wei Zhang
- Yanli Wang
- Yousub Lee
- Yutai Kato
- Adam Stevens
- Andres Marquez Rossy
- Benjamin Lawrie
- Bruce A Pint
- Bryan Lim
- Chengyun Hua
- Christopher Fancher
- Christopher Ledford
- Costas Tsouris
- Dali Wang
- David S Parker
- Gabor Halasz
- Gerry Knapp
- Gordon Robertson
- Gs Jung
- Gyoung Gug Jang
- James A Haynes
- Jay Reynolds
- Jeff Brookins
- Jiaqiang Yan
- Jiheon Jun
- Jong K Keum
- Michael Kirka
- Mina Yoon
- Nicholas Richter
- Patxi Fernandez-Zelaia
- Peter Wang
- Petro Maksymovych
- Priyanshi Agrawal
- Radu Custelcean
- Roger G Miller
- Sarah Graham
- Sumit Bahl
- Sunyong Kwon
- Tim Graening Seibert
- Tomas Grejtak
- Weicheng Zhong
- Wei Tang
- William Peter
- Xiang Chen
- Yan-Ru Lin
- Yiyu Wang
- Yukinori Yamamoto

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

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.

V-Cr-Ti alloys have been proposed as candidate structural materials in fusion reactor blanket concepts with operation temperatures greater than that for reduced activation ferritic martensitic steels (RAFMs).

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 is directed to a machine leaning methodology to quantify the association of a set of input variables to a set of output variables, specifically for the one-to-many scenarios in which the output exhibits a range of variations under the same replicated input condi

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.

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.

When a magnetic field is applied to a type-II superconductor, it penetrates the superconductor in a thin cylindrical line known as a vortex line. Traditional methods to manipulate these vortices are limited in precision and affect a broad area.

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