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Researcher
- Ahmed Hassen
- Brian Post
- Vlastimil Kunc
- Andrzej Nycz
- Peter Wang
- Chris Tyler
- Vipin Kumar
- Chris Masuo
- Corson Cramer
- Costas Tsouris
- Ilias Belharouak
- Soydan Ozcan
- Steve Bullock
- Steven Guzorek
- Vincent Paquit
- Justin West
- Meghan Lamm
- Michelle Kidder
- Ryan Dehoff
- Uday Vaidya
- Umesh N MARATHE
- Andrew Sutton
- David Nuttall
- Greg Larsen
- Halil Tekinalp
- Joshua Vaughan
- Michael Kirka
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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.

The technologies provides for regeneration of anion-exchange resin.
Contact
To learn more about this technology, email partnerships@ornl.gov or call 865-574-1051.

Monoterpenes conversion to C10 aromatics (60%) and C10 cycloalkanes (40%) in an inert environment, provides an established route for sustainable aviation fuel (SAF) blends sourced directly from biomass captured terpenes mixtures.

The technologies provide additively manufactured thermal protection system.

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.

A pressure burst feature has been designed and demonstrated for relieving potentially hazardous excess pressure within irradiation capsules used in the ORNL High Flux Isotope Reactor (HFIR).

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