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Researcher
- Ryan Dehoff
- Michael Kirka
- Soydan Ozcan
- Vincent Paquit
- Xianhui Zhao
- Adam Stevens
- Ahmed Hassen
- Alexander I Wiechert
- Alex Plotkowski
- Alex Roschli
- Alice Perrin
- Amir K Ziabari
- Amit Shyam
- Andres Marquez Rossy
- Benjamin Manard
- Blane Fillingim
- Brian Post
- Charles F Weber
- Christopher Ledford
- Clay Leach
- Costas Tsouris
- David Nuttall
- Erin Webb
- Evin Carter
- Halil Tekinalp
- James Haley
- Jeremy Malmstead
- Joanna Mcfarlane
- Jonathan Willocks
- Kitty K Mccracken
- Louise G Evans
- Matt Vick
- Oluwafemi Oyedeji
- Patxi Fernandez-Zelaia
- Peeyush Nandwana
- Philip Bingham
- Rangasayee Kannan
- Richard L. Reed
- Roger G Miller
- Sanjita Wasti
- Sarah Graham
- Sudarsanam Babu
- Tyler Smith
- Vandana Rallabandi
- Venkatakrishnan Singanallur Vaidyanathan
- Vipin Kumar
- Vlastimil Kunc
- William Peter
- Yan-Ru Lin
- Ying Yang
- Yukinori Yamamoto

We have developed a novel extrusion-based 3D printing technique that can achieve a resolution of 0.51 mm layer thickness, and catalyst loading of 44% and 90.5% before and after drying, respectively.

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 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.

High strength, oxidation resistant refractory alloys are difficult to fabricate for commercial use in extreme environments.

In manufacturing parts for industry using traditional molds and dies, about 70 percent to 80 percent of the time it takes to create a part is a result of a relatively slow cooling process.

This technology combines 3D printing and compression molding to produce high-strength, low-porosity composite articles.

Simurgh revolutionizes industrial CT imaging with AI, enhancing speed and accuracy in nondestructive testing for complex parts, reducing costs.

An innovative low-cost system for in-situ monitoring of strain and temperature during directed energy deposition.