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Researcher
- Hongbin Sun
- Stephen M Killough
- Ben Lamm
- Beth L Armstrong
- Bruce A Pint
- Bryan Maldonado Puente
- Corey Cooke
- Diana E Hun
- Ilias Belharouak
- Meghan Lamm
- Nolan Hayes
- Peter Wang
- Philip Boudreaux
- Pradeep Ramuhalli
- Praveen Cheekatamarla
- Ruhul Amin
- Ryan Kerekes
- Sally Ghanem
- Shajjad Chowdhury
- Steven J Zinkle
- Tim Graening Seibert
- Tolga Aytug
- Vishaldeep Sharma
- Weicheng Zhong
- Wei Tang
- Xiang Chen
- Yanli Wang
- Ying Yang
- Yutai Kato

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.

New demands in electric vehicles have resulted in design changes for the power electronic components such as the capacitor to incur lower volume, higher operating temperatures, and dielectric properties (high dielectric permittivity and high electrical breakdown strengths).

The first wall and blanket of a fusion energy reactor must maintain structural integrity and performance over long operational periods under neutron irradiation and minimize long-lived radioactive waste.

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.

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).

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