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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.

Here we present a solution for practically demonstrating path-aware routing and visualizing a self-driving network.

Technologies directed to polarization agnostic continuous variable quantum key distribution are described.
Contact:
To learn more about this technology, email partnerships@ornl.gov or call 865-574-1051.

The development of quantum networking requires architectures capable of dynamically reconfigurable entanglement distribution to meet diverse user needs and ensure tolerance against transmission disruptions.

Wind turbine blades face a harsh environment in which erosion of the leading edge is a major factor for in-use maintenance. Current industrial practices to address this leading edge erosion are replacement of reinforcing materials upon significant damage infliction.

System and method for part porosity monitoring of additively manufactured components using machining
In additive manufacturing, choice of process parameters for a given material and geometry can result in porosities in the build volume, which can result in scrap.

We have been working to adapt background oriented schlieren (BOS) imaging to directly visualize building leakage, which is fast and easy.

Through utilizing a two function splice we can increase the splice strength for opposing tows.
Contact:
To learn more about this technology, email partnerships@ornl.gov or call 865-574-1051.

Polarization drift in quantum networks is a major issue. Fiber transforms a transmitted signal’s polarization differently depending on its environment.

We proposed and developed a carbon nanofiber (CNF) suspension-based sizing agent, that resulted in improved interfacial, and mechanical properties. The CNF dispersed sizing agent can be applied in a relatively simpler way (by passing the continuous tow through it).