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Researcher
- Kyle Kelley
- Rama K Vasudevan
- Sergei V Kalinin
- Stephen Jesse
- Alexander I Kolesnikov
- An-Ping Li
- Andrew Lupini
- Anton Ievlev
- Bekki Mills
- Bogdan Dryzhakov
- Bruce Moyer
- Debjani Pal
- Hoyeon Jeon
- Huixin (anna) Jiang
- Jamieson Brechtl
- Jeffrey Einkauf
- Jennifer M Pyles
- Jewook Park
- John Wenzel
- Kai Li
- Kashif Nawaz
- Kevin M Roccapriore
- Kuntal De
- Laetitia H Delmau
- Liam Collins
- Luke Sadergaski
- Mark Loguillo
- Marti Checa Nualart
- Matthew B Stone
- Maxim A Ziatdinov
- Neus Domingo Marimon
- Olga S Ovchinnikova
- Ondrej Dyck
- Saban Hus
- Steven Randolph
- Victor Fanelli
- Yongtao Liu

Ruthenium is recovered from used nuclear fuel in an oxidizing environment by depositing the volatile RuO4 species onto a polymeric substrate.

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

Neutron scattering experiments cover a large temperature range in which experimenters want to test their samples.

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

Distortion in scanning tunneling microscope (STM) images is an unavoidable problem. This technology is an algorithm to identify and correct distorted wavefronts in atomic resolution STM images.

Neutron beams are used around the world to study materials for various purposes.

Moisture management accounts for over 40% of the energy used by buildings. As such development of energy efficient and resilient dehumidification technologies are critical to decarbonize the building energy sector.

This technology provides a device, platform and method of fabrication of new atomically tailored materials. This “synthescope” is a scanning transmission electron microscope (STEM) transformed into an atomic-scale material manipulation platform.

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