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Researcher
- Kyle Kelley
- Rama K Vasudevan
- Yong Chae Lim
- Rangasayee Kannan
- Sergei V Kalinin
- Adam Stevens
- Anton Ievlev
- Bogdan Dryzhakov
- Brian Post
- Bryan Lim
- Govindarajan Muralidharan
- 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
- Rose Montgomery
- Ryan Dehoff
- Sarah Graham
- Stephen Jesse
- Steven Randolph
- Sudarsanam Babu
- Thomas R Muth
- Tomas Grejtak
- Venugopal K Varma
- William Peter
- Yiyu Wang
- Yongtao Liu
- 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.

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.

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.

This invention introduces a system for microscopy called pan-sharpening, enabling the generation of images with both full-spatial and full-spectral resolution without needing to capture the entire dataset, significantly reducing data acquisition time.

The need for accurate temperature measurement in critical environments such as nuclear reactors is paramount for safety and efficiency.