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Researcher
- Amit Shyam
- Alex Plotkowski
- Amit K Naskar
- Yong Chae Lim
- Zhili Feng
- James A Haynes
- Jaswinder Sharma
- Jian Chen
- Logan Kearney
- Michael Toomey
- Nihal Kanbargi
- Peeyush Nandwana
- Rangasayee Kannan
- Ryan Dehoff
- Sumit Bahl
- Wei Zhang
- Adam Stevens
- Alice Perrin
- Andres Marquez Rossy
- Arit Das
- Benjamin L Doughty
- Brian Post
- Bryan Lim
- Christopher Bowland
- Christopher Fancher
- Dali Wang
- Dean T Pierce
- Edgar Lara-Curzio
- Felix L Paulauskas
- Frederic Vautard
- Gerry Knapp
- Gordon Robertson
- Holly Humphrey
- Jay Reynolds
- Jeff Brookins
- Jiheon Jun
- Jovid Rakhmonov
- Nicholas Richter
- Peter Wang
- Priyanshi Agrawal
- Robert E Norris Jr
- Roger G Miller
- Santanu Roy
- Sarah Graham
- Sudarsanam Babu
- Sumit Gupta
- Sunyong Kwon
- Tomas Grejtak
- Uvinduni Premadasa
- Vera Bocharova
- William Peter
- Ying Yang
- Yiyu Wang
- Yukinori Yamamoto

Efficient thermal management in polymers is essential for developing lightweight, high-strength materials with multifunctional capabilities.

The disclosure is directed to optimized fiber geometries for use in carbon fiber reinforced polymers with increased compressive strength per unit cost. The disclosed fiber geometries reduce the material processing costs as well as increase the compressive strength.

A finite element approach integrated with a novel constitute model to predict phase change, residual stresses and part deformation.

Currently available cast Al alloys are not suitable for various high-performance conductor applications, such as rotor, inverter, windings, busbar, heat exchangers/sinks, etc.

The invented alloys are a new family of Al-Mg alloys. This new family of Al-based alloys demonstrate an excellent ductility (10 ± 2 % elongation) despite the high content of impurities commonly observed in recycled aluminum.

A novel and cost-effective process for the activation of carbon fibers was established.
Contact
To learn more about this technology, email partnerships@ornl.gov or call 865-574-1051.

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.

This invention is directed to a machine leaning methodology to quantify the association of a set of input variables to a set of output variables, specifically for the one-to-many scenarios in which the output exhibits a range of variations under the same replicated input condi

A new nanostructured bainitic steel with accelerated kinetics for bainite formation at 200 C was designed using a coupled CALPHAD, machine learning, and data mining approach.