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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.
High-gradient magnetic filtration (HGMF) is a non-destructive separation technique that captures magnetic constituents from a matrix containing other non-magnetic species. One characteristic that actinide metals share across much of the group is that they are magnetic.
We have been working to adapt background oriented schlieren (BOS) imaging to directly visualize building leakage, which is fast and easy.
Neutron scattering experiments cover a large temperature range in which experimenters want to test their samples.
Pyrolysis evolved gas analysis – mass spectrometry (EGA-MS) and pyrolysis gas chromatography – MS (GC-MS) – are powerful analytical tools for polymer characterization.
Neutron beams are used around the world to study materials for various purposes.
We have developed an aerosol sampling technique to enable collection of trace materials such as actinides in the atmosphere.
Simurgh revolutionizes industrial CT imaging with AI, enhancing speed and accuracy in nondestructive testing for complex parts, reducing costs.