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Researcher
- Kyle Kelley
- Rama K Vasudevan
- Yong Chae Lim
- Rangasayee Kannan
- Sergei V Kalinin
- Aaron Werth
- Adam Stevens
- Ali Passian
- Anton Ievlev
- Bogdan Dryzhakov
- Brian Post
- Bryan Lim
- Emilio Piesciorovsky
- Gary Hahn
- Harper Jordan
- Jiheon Jun
- Joel Asiamah
- Joel Dawson
- Kevin M Roccapriore
- Liam Collins
- Marti Checa Nualart
- Maxim A Ziatdinov
- Nance Ericson
- Neus Domingo Marimon
- Olga S Ovchinnikova
- Peeyush Nandwana
- Priyanshi Agrawal
- Raymond Borges Hink
- Roger G Miller
- Ryan Dehoff
- Sarah Graham
- Srikanth Yoginath
- Stephen Jesse
- Steven Randolph
- Sudarsanam Babu
- Tomas Grejtak
- Varisara Tansakul
- William Peter
- Yarom Polsky
- 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.

Electrical utility substations are wired with intelligent electronic devices (IEDs), such as protective relays, power meters, and communication switches.

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.