1 - 10 of 16 Results
ORNL researchers have developed a deep learning-based approach to rapidly perform high-quality reconstructions from sparse X-ray computed tomography measurements.
Ruthenium is recovered from used nuclear fuel in an oxidizing environment by depositing the volatile RuO4 species onto a polymeric substrate.
We have been working to adapt background oriented schlieren (BOS) imaging to directly visualize building leakage, which is fast and easy.
V-Cr-Ti alloys have been proposed as candidate structural materials in fusion reactor blanket concepts with operation temperatures greater than that for reduced activation ferritic martensitic steels (RAFMs).
Fusion reactors need efficient systems to create tritium fuel and handle intense heat and radiation. Traditional liquid metal systems face challenges like high pressure losses and material breakdown in strong magnetic fields.
The traditional window installation process involves many steps. These are becoming even more complex with newer construction requirements such as installation of windows over exterior continuous insulation walls.
Spherical powders applied to nuclear targetry for isotope production will allow for enhanced heat transfer properties, tailored thermal conductivity and minimize time required for target fabrication and post processing.
This invention utilizes new techniques in machine learning to accelerate the training of ML-based communication receivers.
Biocompatible nanoparticles have been developed that can trap and retain therapeutic radionuclides and their byproducts at the cancer site. This is important to maximize the therapeutic effect of this treatment and minimize associated side effects.
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).