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Researcher
- Diana E Hun
- Singanallur Venkatakrishnan
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- Obaid Rahman
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- Ryan Kerekes
- Sally Ghanem
- Tomonori Saito
- Zoriana Demchuk

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.

Estimates based on the U.S. Department of Energy (DOE) test procedure for water heaters indicate that the equivalent of 350 billion kWh worth of hot water is discarded annually through drains, and a large portion of this energy is, in fact, recoverable.

The incorporation of low embodied carbon building materials in the enclosure is increasing the fuel load for fire, increasing the demand for fire/flame retardants.

This technology is a laser-based heating unit that offers rapid heating profiles on a research scale with minimal incidental heating of materials processing environments.

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).