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Researcher
- Ahmed Hassen
- Vlastimil Kunc
- Steven Guzorek
- Ali Passian
- Vipin Kumar
- Brian Post
- David Nuttall
- Singanallur Venkatakrishnan
- Soydan Ozcan
- Amir K Ziabari
- Dan Coughlin
- Jim Tobin
- Philip Bingham
- Pum Kim
- Ryan Dehoff
- Segun Isaac Talabi
- Tyler Smith
- Uday Vaidya
- Umesh N MARATHE
- Vincent Paquit
- Adam Stevens
- Alex Roschli
- Brittany Rodriguez
- Claire Marvinney
- Craig Blue
- Diana E Hun
- Erin Webb
- Evin Carter
- Georges Chahine
- Gina Accawi
- Gurneesh Jatana
- Halil Tekinalp
- Harper Jordan
- Jeremy Malmstead
- Joel Asiamah
- Joel Dawson
- John Lindahl
- Josh Crabtree
- Julian Charron
- Katie Copenhaver
- Kim Sitzlar
- Kitty K Mccracken
- Komal Chawla
- Mark M Root
- Merlin Theodore
- Michael Kirka
- Nadim Hmeidat
- Nance Ericson
- Obaid Rahman
- Oluwafemi Oyedeji
- Philip Boudreaux
- Ryan Ogle
- Sana Elyas
- Srikanth Yoginath
- Steve Bullock
- Subhabrata Saha
- Sudarsanam Babu
- Thomas Feldhausen
- Varisara Tansakul
- Xianhui Zhao

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

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

This manufacturing method uses multifunctional materials distributed volumetrically to generate a stiffness-based architecture, where continuous surfaces can be created from flat, rapidly produced geometries.

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.

The use of biomass fiber reinforcement for polymer composite applications, like those in buildings or automotive, has expanded rapidly due to the low cost, high stiffness, and inherent renewability of these materials. Biomass are commonly disposed of as waste.