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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.

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.

The technology describes an electron beam in a storage ring as a quantum computer.

Simurgh revolutionizes industrial CT imaging with AI, enhancing speed and accuracy in nondestructive testing for complex parts, reducing costs.

An ORNL team has developed a method for screening for an immunoregulatory protein, which includes assessing the sequence of a candidate protein to determine if it is an immunoregulatory protein when at least one plasminogen-apple-nematode (PAN) domain with a consensus sequence