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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.
The invention discloses methods of using a reducing agent for catalytic oxygen reduction from CO2 streams, enabling the treated CO2 streams to meet the pipeline specifications.
An electrochemical cell has been specifically designed to maximize CO2 release from the seawater while also not changing the pH of the seawater before returning to the sea.
Lean-burn natural gas (NG) engines are a preferred choice for the hard-to-electrify sectors for higher efficiency and lower NOx emissions, but methane slip can be a challenge.
Simurgh revolutionizes industrial CT imaging with AI, enhancing speed and accuracy in nondestructive testing for complex parts, reducing costs.
This innovative approach combines optical and spectral imaging data via machine learning to accurately predict cancer labels directly from tissue images.