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Researcher
- Kyle Kelley
- Rama K Vasudevan
- Yong Chae Lim
- Rangasayee Kannan
- Sergei V Kalinin
- Zhili Feng
- Adam Stevens
- Anton Ievlev
- Bogdan Dryzhakov
- Brian Post
- Bryan Lim
- Femi Omitaomu
- Haowen Xu
- Jian Chen
- Jiheon Jun
- Kevin M Roccapriore
- Liam Collins
- Marti Checa Nualart
- Maxim A Ziatdinov
- Neus Domingo Marimon
- Olga S Ovchinnikova
- Peeyush Nandwana
- Priyanshi Agrawal
- Roger G Miller
- Ryan Dehoff
- Sarah Graham
- Stephen Jesse
- Steven Randolph
- Sudarsanam Babu
- Tomas Grejtak
- Wei Zhang
- William Peter
- Yiyu Wang
- Yongtao Liu
- Yukinori Yamamoto

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

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 invention introduces a novel, customizable method to create, manipulate, and erase polar topological structures in ferroelectric materials using atomic force microscopy.

High coercive fields prevalent in wurtzite ferroelectrics present a significant challenge, as they hinder efficient polarization switching, which is essential for microelectronic applications.

We will develop an AI-powered autonomous software development pipeline to help urban scientists develop advanced research software (e.g., digital twins and cyberinfrastructure) to support smart city research and management without the need to write codes or know software engin

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.

This invention presents technologies for characterizing physical properties of a sample's surface by combining image processing with machine learning techniques.