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Researcher
- Yong Chae Lim
- Zhili Feng
- Jian Chen
- Rangasayee Kannan
- Wei Zhang
- Adam Stevens
- Brian Post
- Bruce Moyer
- Bryan Lim
- Dali Wang
- Debjani Pal
- Felipe Polo Garzon
- Jeffrey Einkauf
- Jennifer M Pyles
- Jiheon Jun
- Junyan Zhang
- Justin Griswold
- Kuntal De
- Laetitia H Delmau
- Luke Sadergaski
- Mike Zach
- Padhraic L Mulligan
- Peeyush Nandwana
- Priyanshi Agrawal
- Roger G Miller
- Ryan Dehoff
- Sandra Davern
- Sarah Graham
- Sudarsanam Babu
- Tomas Grejtak
- William Peter
- Yiyu Wang
- Yukinori Yamamoto

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

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

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.

Spherical powders applied to nuclear targetry for isotope production will allow for enhanced heat transfer properties, tailored thermal conductivity and minimize time required for target fabrication and post processing.

The technologies provide a coating method to produce corrosion resistant and electrically conductive coating layer on metallic bipolar plates for hydrogen fuel cell and hydrogen electrolyzer applications.

Welding high temperature and/or high strength materials for aerospace or automobile manufacturing is challenging.