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Researcher
- Alex Plotkowski
- Amit Shyam
- Peeyush Nandwana
- Ryan Dehoff
- Venkatakrishnan Singanallur Vaidyanathan
- Amir K Ziabari
- Blane Fillingim
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- Philip Bingham
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- Sudarsanam Babu
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- Yousub Lee
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- John Holliman II
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- Mark M Root
- Md Inzamam Ul Haque
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- Nicholas Richter
- Nolan Hayes
- Obaid Rahman
- Olga S Ovchinnikova
- Peter Wang
- Radu Custelcean
- Ramanan Sankaran
- Ryan Kerekes
- Sally Ghanem
- Sunyong Kwon
- Vimal Ramanuj
- Wenjun Ge
- Ying Yang

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.

Currently available cast Al alloys are not suitable for various high-performance conductor applications, such as rotor, inverter, windings, busbar, heat exchangers/sinks, etc.

The invented alloys are a new family of Al-Mg alloys. This new family of Al-based alloys demonstrate an excellent ductility (10 ± 2 % elongation) despite the high content of impurities commonly observed in recycled aluminum.

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

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.