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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.
A pressure burst feature has been designed and demonstrated for relieving potentially hazardous excess pressure within irradiation capsules used in the ORNL High Flux Isotope Reactor (HFIR).
We have been working to adapt background oriented schlieren (BOS) imaging to directly visualize building leakage, which is fast and easy.
We developed and incorporated two innovative mPET/Cu and mPET/Al foils as current collectors in LIBs to enhance cell energy density under XFC conditions.
Sintering additives to improve densification and microstructure control of UN provides a facile approach to producing high quality nuclear fuels.
The co-processing of cathode and composite electrolyte for solid state polymer batteries has been developed. A traditional uncalendared cathode of e.g.
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.
This technology is a strategy for decreasing electromagnetic interference and boosting signal fidelity for low signal-to-noise sensors transmitting over long distances in extreme environments, such as nuclear energy generation applications, particularly for particle detection.
Simurgh revolutionizes industrial CT imaging with AI, enhancing speed and accuracy in nondestructive testing for complex parts, reducing costs.