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Researcher
- Singanallur Venkatakrishnan
- Amir K Ziabari
- Andrzej Nycz
- Chris Masuo
- Diana E Hun
- Luke Meyer
- Peter Wang
- Philip Bingham
- Philip Boudreaux
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- Vincent Paquit
- William Carter
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- Bruce Hannan
- Bryan Maldonado Puente
- Corey Cooke
- Costas Tsouris
- Gina Accawi
- Gs Jung
- Gurneesh Jatana
- Gyoung Gug Jang
- Jong K Keum
- Joshua Vaughan
- Loren L Funk
- Mark M Root
- Michael Kirka
- Mina Yoon
- Nolan Hayes
- Obaid Rahman
- Polad Shikhaliev
- Radu Custelcean
- Ryan Kerekes
- Sally Ghanem
- Theodore Visscher
- Vladislav N Sedov
- Yacouba Diawara

ORNL researchers have developed a deep learning-based approach to rapidly perform high-quality reconstructions from sparse X-ray computed tomography measurements.

We have been working to adapt background oriented schlieren (BOS) imaging to directly visualize building leakage, which is fast and easy.

ORNL has developed a large area thermal neutron detector based on 6LiF/ZnS(Ag) scintillator coupled with wavelength shifting fibers. The detector uses resistive charge divider-based position encoding.

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

A novel molecular sorbent system for low energy CO2 regeneration is developed by employing CO2-responsive molecules and salt in aqueous media where a precipitating CO2--salt fractal network is formed, resulting in solid-phase formation and sedimentation.

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.