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Researcher
- Singanallur Venkatakrishnan
- Amir K Ziabari
- Diana E Hun
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- Tolga Aytug
- Tyler Gerczak
- Weicheng Zhong
- Wei Tang
- Xiang Chen
- Yanli Wang
- Ying Yang
- Yutai Kato

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.

Sintering additives to improve densification and microstructure control of UN provides a facile approach to producing high quality nuclear fuels.

New demands in electric vehicles have resulted in design changes for the power electronic components such as the capacitor to incur lower volume, higher operating temperatures, and dielectric properties (high dielectric permittivity and high electrical breakdown strengths).

The first wall and blanket of a fusion energy reactor must maintain structural integrity and performance over long operational periods under neutron irradiation and minimize long-lived radioactive waste.

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

The use of Fluidized Bed Chemical Vapor Deposition to coat particles or fibers is inherently slow and capital intensive, as it requires constant modifications to the equipment to account for changes in the characteristics of the substrates to be coated.

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.