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Researcher
- Peeyush Nandwana
- Amit K Naskar
- Brian Post
- Rangasayee Kannan
- Sudarsanam Babu
- Yong Chae Lim
- Zhili Feng
- Amit Shyam
- Blane Fillingim
- Jaswinder Sharma
- Jian Chen
- Lauren Heinrich
- Logan Kearney
- Michael Toomey
- Nihal Kanbargi
- Ryan Dehoff
- Thomas Feldhausen
- Wei Zhang
- Yousub Lee
- Adam Stevens
- Alex Plotkowski
- Andres Marquez Rossy
- Arit Das
- Benjamin L Doughty
- Bruce A Pint
- Bryan Lim
- Christopher Bowland
- Christopher Fancher
- Dali Wang
- Edgar Lara-Curzio
- Felix L Paulauskas
- Frederic Vautard
- Gordon Robertson
- Holly Humphrey
- Jay Reynolds
- Jeff Brookins
- Jiheon Jun
- Peter Wang
- Priyanshi Agrawal
- Robert E Norris Jr
- Roger G Miller
- Santanu Roy
- Sarah Graham
- Steven J Zinkle
- Sumit Gupta
- Tim Graening Seibert
- Tomas Grejtak
- Uvinduni Premadasa
- Vera Bocharova
- Weicheng Zhong
- Wei Tang
- William Peter
- Xiang Chen
- Yanli Wang
- Ying Yang
- Yiyu Wang
- Yukinori Yamamoto
- Yutai Kato

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.

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.

ORNL contributes to developing the concept of passive CO2 DAC by designing and testing a hybrid sorption system. This design aims to leverage the advantages of CO2 solubility and selectivity offered by materials with selective sorption of adsorbents.

This work seeks to alter the interface condition through thermal history modification, deposition energy density, and interface surface preparation to prevent interface cracking.

Additive manufacturing (AM) enables the incremental buildup of monolithic components with a variety of materials, and material deposition locations.