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Researcher
- Amit Shyam
- Alex Plotkowski
- Yong Chae Lim
- Zhili Feng
- James A Haynes
- Jian Chen
- Peeyush Nandwana
- Rangasayee Kannan
- Ryan Dehoff
- Sumit Bahl
- Wei Zhang
- Adam Stevens
- Alice Perrin
- Andres Marquez Rossy
- Brian Post
- Brian Sanders
- Bryan Lim
- Christopher Fancher
- Dali Wang
- Dean T Pierce
- Gerald Tuskan
- Gerry Knapp
- Gordon Robertson
- Ilenne Del Valle Kessra
- Isaiah Dishner
- Jay Reynolds
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- Jerry Parks
- Jiheon Jun
- John F Cahill
- Josh Michener
- Jovid Rakhmonov
- Liangyu Qian
- Nicholas Richter
- Paul Abraham
- Peter Wang
- Priyanshi Agrawal
- Roger G Miller
- Sarah Graham
- Sudarsanam Babu
- Sunyong Kwon
- Tomas Grejtak
- Vilmos Kertesz
- William Peter
- Xiaohan Yang
- Yang Liu
- Ying Yang
- Yiyu Wang
- Yukinori Yamamoto

Enzymes for synthesis of sequenced oligoamide triads and tetrads that can be polymerized into sequenced copolyamides.
Contact
To learn more about this technology, email partnerships@ornl.gov or call 865-574-1051.

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.

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.

Detection of gene expression in plants is critical for understanding the molecular basis of plant physiology and plant responses to drought, stress, climate change, microbes, insects and other factors.

The technologies provide a coating method to produce corrosion resistant and electrically conductive coating layer on metallic bipolar plates for hydrogen fuel cell and hydrogen electrolyzer applications.