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Researcher
- Kyle Kelley
- Rama K Vasudevan
- Hongbin Sun
- Prashant Jain
- Sergei V Kalinin
- Stephen Jesse
- Stephen M Killough
- An-Ping Li
- Andrew Lupini
- Anton Ievlev
- Bogdan Dryzhakov
- Bryan Maldonado Puente
- Corey Cooke
- Diana E Hun
- Hoyeon Jeon
- Huixin (anna) Jiang
- Ian Greenquist
- Ilias Belharouak
- Jamieson Brechtl
- Jewook Park
- Kai Li
- Kashif Nawaz
- Kevin M Roccapriore
- Liam Collins
- Marti Checa Nualart
- Maxim A Ziatdinov
- Nate See
- Neus Domingo Marimon
- Nithin Panicker
- Nolan Hayes
- Olga S Ovchinnikova
- Ondrej Dyck
- Peter Wang
- Philip Boudreaux
- Pradeep Ramuhalli
- Praveen Cheekatamarla
- Ruhul Amin
- Ryan Kerekes
- Saban Hus
- Sally Ghanem
- Steven Randolph
- Vishaldeep Sharma
- Vittorio Badalassi
- Yongtao Liu

The invention presented here addresses key challenges associated with counterfeit refrigerants by ensuring safety, maintaining system performance, supporting environmental compliance, and mitigating health and legal risks.

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.

A novel approach is presented herein to improve time to onset of natural convection stemming from fuel element porosity during a failure mode of a nuclear reactor.

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.

Recent advances in magnetic fusion (tokamak) technology have attracted billions of dollars of investments in startups from venture capitals and corporations to develop devices demonstrating net energy gain in a self-heated burning plasma, such as SPARC (under construction) and

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

Knowing the state of charge of lithium-ion batteries, used to power applications from electric vehicles to medical diagnostic equipment, is critical for long-term battery operation.