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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.
High strength, oxidation resistant refractory alloys are difficult to fabricate for commercial use in extreme environments.
In order to avoid the limitations and costs due to the use of monolithic components for chemical vapor deposition, we developed a modular system in which the reaction chamber can be composed of a top and bottom cone, nozzle, and in-situ reaction chambers.
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.
In manufacturing parts for industry using traditional molds and dies, about 70 percent to 80 percent of the time it takes to create a part is a result of a relatively slow cooling process.
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).