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Researcher
- Yong Chae Lim
- Rangasayee Kannan
- Stephen M Killough
- Vlastimil Kunc
- Adam Stevens
- Ahmed Hassen
- Brian Post
- Bryan Lim
- Bryan Maldonado Puente
- Corey Cooke
- Dan Coughlin
- Diana E Hun
- Jiheon Jun
- Jim Tobin
- Josh Crabtree
- Kim Sitzlar
- Merlin Theodore
- Nolan Hayes
- Peeyush Nandwana
- Peter Wang
- Philip Boudreaux
- Priyanshi Agrawal
- Roger G Miller
- Ryan Dehoff
- Ryan Kerekes
- Sally Ghanem
- Sarah Graham
- Steven Guzorek
- Subhabrata Saha
- Sudarsanam Babu
- Tomas Grejtak
- Vipin Kumar
- William Peter
- Yiyu Wang
- Yukinori Yamamoto
- Zhili Feng

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.

Through the use of splicing methods, joining two different fiber types in the tow stage of the process enables great benefits to the strength of the material change.

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

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.

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).