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- Venkatakrishnan Singanallur Vaidyanathan
- Alexander I Wiechert
- Amir K Ziabari
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- Lauren Heinrich
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- Md Inzamam Ul Haque
- Michael Kirka
- Mingyan Li
- Nolan Hayes
- Obaid Rahman
- Olga S Ovchinnikova
- Oscar Martinez
- Peter Wang
- Radu Custelcean
- Ramanan Sankaran
- Rose Montgomery
- Ryan Kerekes
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- Sam Hollifield
- Thomas R Muth
- Vandana Rallabandi
- Venugopal K Varma
- Vimal Ramanuj
- Wenjun Ge

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

How fast is a vehicle traveling? For different reasons, this basic question is of interest to other motorists, insurance companies, law enforcement, traffic planners, and security personnel. Solutions to this measurement problem suffer from a number of constraints.

High-gradient magnetic filtration (HGMF) is a non-destructive separation technique that captures magnetic constituents from a matrix containing other non-magnetic species. One characteristic that actinide metals share across much of the group is that they are magnetic.

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

The lattice collimator places a grid of shielding material in front of a radiation detector to reduce the effect of background from surrounding materials and to enhance the RPM sensitivity to point sources rather than distributed sources that are commonly associated with Natur

Among the methods for point source carbon capture, the absorption of CO2 using aqueous amines (namely MEA) from the post-combustion gas stream is currently considered the most promising.

This work seeks to alter the interface condition through thermal history modification, deposition energy density, and interface surface preparation to prevent interface cracking.

Additive manufacturing (AM) enables the incremental buildup of monolithic components with a variety of materials, and material deposition locations.

Ceramic matrix composites are used in several industries, such as aerospace, for lightweight, high quality and high strength materials. But producing them is time consuming and often low quality.

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