Available Technologies

ORNL researchers have developed a deep learning-based approach to rapidly perform high-quality reconstructions from sparse X-ray computed tomography measurements. 

We presented a novel apparatus and method for laser beam position detection and pointing stabilization using analog position-sensitive diodes (PSDs).

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.

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.

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). 

The lack of real-time insights into how materials evolve during laser powder bed fusion has limited the adoption by inhibiting part qualification.  The developed approach provides key data needed to fabricate born qualified parts.

ORNL has developed a large area thermal neutron detector based on 6LiF/ZnS(Ag) scintillator coupled with wavelength shifting fibers. The detector uses resistive charge divider-based position encoding.

The technologies polymer cellulose nanocomposite mats and process for making same.

Contact

To learn more about this technology, email partnerships@ornl.gov or call 865-574-1051.