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Researcher
- Ryan Dehoff
- Kyle Kelley
- Rama K Vasudevan
- Michael Kirka
- Sergei V Kalinin
- Stephen M Killough
- Vincent Paquit
- Adam Stevens
- Ahmed Hassen
- Alex Plotkowski
- Alice Perrin
- Amir K Ziabari
- Amit Shyam
- Andres Marquez Rossy
- Anton Ievlev
- Blane Fillingim
- Bogdan Dryzhakov
- Brian Post
- Bryan Maldonado Puente
- Christopher Ledford
- Clay Leach
- Corey Cooke
- David Nuttall
- Diana E Hun
- James Haley
- Kevin M Roccapriore
- Liam Collins
- Marti Checa Nualart
- Maxim A Ziatdinov
- Neus Domingo Marimon
- Nolan Hayes
- Olga S Ovchinnikova
- Patxi Fernandez-Zelaia
- Peeyush Nandwana
- Peter Wang
- Philip Bingham
- Philip Boudreaux
- Rangasayee Kannan
- Roger G Miller
- Ryan Kerekes
- Sally Ghanem
- Sarah Graham
- Singanallur Venkatakrishnan
- Stephen Jesse
- Steven Randolph
- Sudarsanam Babu
- Vipin Kumar
- Vlastimil Kunc
- William Peter
- Yan-Ru Lin
- Ying Yang
- Yongtao Liu
- Yukinori Yamamoto

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.

High strength, oxidation resistant refractory alloys are difficult to fabricate for commercial use in extreme environments.

This invention utilizes new techniques in machine learning to accelerate the training of ML-based communication receivers.

In manufacturing parts for industry using traditional molds and dies, about 70 percent to 80 percent of the time it takes to create a part is a result of a relatively slow cooling process.

Current technology for heating, ventilation, and air conditioning (HVAC) and other uses such as vending machines rely on refrigerants that have high global warming potential (GWP).

This technology combines 3D printing and compression molding to produce high-strength, low-porosity composite articles.

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