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Researcher
- Yong Chae Lim
- Hongbin Sun
- Rangasayee Kannan
- Adam Stevens
- Alexander I Wiechert
- Brian Post
- Bryan Lim
- Costas Tsouris
- Debangshu Mukherjee
- Gs Jung
- Gyoung Gug Jang
- Ilias Belharouak
- Jiheon Jun
- Md Inzamam Ul Haque
- Olga S Ovchinnikova
- Peeyush Nandwana
- Pradeep Ramuhalli
- Praveen Cheekatamarla
- Priyanshi Agrawal
- Radu Custelcean
- Roger G Miller
- Ruhul Amin
- Ryan Dehoff
- Sarah Graham
- Sudarsanam Babu
- Tomas Grejtak
- Vishaldeep Sharma
- William Peter
- Yiyu Wang
- Yukinori Yamamoto
- Zhili Feng

The invention presented here addresses key challenges associated with counterfeit refrigerants by ensuring safety, maintaining system performance, supporting environmental compliance, and mitigating health and legal risks.

Among the methods for point source carbon capture, the absorption of CO2 using aqueous amines (namely MEA) from the post-combustion gas stream is currently considered the most promising.

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.

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.

Knowing the state of charge of lithium-ion batteries, used to power applications from electric vehicles to medical diagnostic equipment, is critical for long-term battery operation.

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

This innovative approach combines optical and spectral imaging data via machine learning to accurately predict cancer labels directly from tissue images.