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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.
We tested 48 diverse homologs of SfaB and identified several enzyme variants that were more active than SfaB at synthesizing the nylon-6,6 monomer.
We have been working to adapt background oriented schlieren (BOS) imaging to directly visualize building leakage, which is fast and easy.
When a magnetic field is applied to a type-II superconductor, it penetrates the superconductor in a thin cylindrical line known as a vortex line. Traditional methods to manipulate these vortices are limited in precision and affect a broad area.
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.