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Researcher
- Hongbin Sun
- Stephen M Killough
- Alexander I Kolesnikov
- Alexei P Sokolov
- Bekki Mills
- Bryan Maldonado Puente
- Corey Cooke
- Diana E Hun
- Ilias Belharouak
- John Wenzel
- Keju An
- Mark Loguillo
- Matthew B Stone
- Nolan Hayes
- Peter Wang
- Philip Boudreaux
- Pradeep Ramuhalli
- Praveen Cheekatamarla
- Ruhul Amin
- Ryan Kerekes
- Sally Ghanem
- Shannon M Mahurin
- Tao Hong
- Thien D. Nguyen
- Tomonori Saito
- Victor Fanelli
- Vishaldeep Sharma

In nuclear and industrial facilities, fine particles, including radioactive residues—can accumulate on the interior surfaces of ventilation ducts and equipment, posing serious safety and operational risks.

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.

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

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

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).