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Researcher
- Yong Chae Lim
- Rangasayee Kannan
- Zhili Feng
- Adam Stevens
- Alexander I Wiechert
- Brian Post
- Brian Sanders
- Bryan Lim
- Costas Tsouris
- Debangshu Mukherjee
- Gs Jung
- Gyoung Gug Jang
- Jerry Parks
- Jian Chen
- Jiheon Jun
- Md Inzamam Ul Haque
- Olga S Ovchinnikova
- Peeyush Nandwana
- Priyanshi Agrawal
- Radu Custelcean
- Roger G Miller
- Ryan Dehoff
- Sarah Graham
- Sudarsanam Babu
- Tomas Grejtak
- Wei Zhang
- 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.

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.

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

Direct-acting antivirals are needed to combat coronavirus disease 2019 (COVID-19), which is caused by severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2).

There is a critical need for new antiviral drugs for treating infections of severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2).

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