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Researcher
- Kyle Kelley
- Rama K Vasudevan
- Sergei V Kalinin
- Stephen M Killough
- Alexander I Wiechert
- Anton Ievlev
- Benjamin Manard
- Bogdan Dryzhakov
- Bryan Maldonado Puente
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- Kunal Mondal
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- Mahim Mathur
- Marti Checa Nualart
- Matt Vick
- Maxim A Ziatdinov
- Mingyan Li
- Neus Domingo Marimon
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- Olga S Ovchinnikova
- Oscar Martinez
- Peter Wang
- Philip Boudreaux
- Rose Montgomery
- Ryan Kerekes
- Sally Ghanem
- Sam Hollifield
- Stephen Jesse
- Steven Randolph
- Thomas R Muth
- Vandana Rallabandi
- Venugopal K Varma
- Yongtao Liu

High-gradient magnetic filtration (HGMF) is a non-destructive separation technique that captures magnetic constituents from a matrix containing other non-magnetic species. One characteristic that actinide metals share across much of the group is that they are magnetic.

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.

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

Real-time tracking and monitoring of radioactive/nuclear materials during transportation is a critical need to ensure safety and security. Current technologies rely on simple tagging, using sensors attached to transport containers, but they have limitations.

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

Technologies for optimizing prefab retrofit panel installation using a real-time evaluator is described.

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.