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Researcher
- Amit K Naskar
- Yong Chae Lim
- Zhili Feng
- Jaswinder Sharma
- Jian Chen
- Logan Kearney
- Michael Toomey
- Nihal Kanbargi
- Rangasayee Kannan
- Wei Zhang
- Adam Stevens
- Arit Das
- Benjamin L Doughty
- Brian Post
- Bruce Moyer
- Bryan Lim
- Christopher Bowland
- Dali Wang
- Debjani Pal
- Edgar Lara-Curzio
- Felix L Paulauskas
- Frederic Vautard
- Holly Humphrey
- Jeffrey Einkauf
- Jennifer M Pyles
- Jiheon Jun
- Justin Griswold
- Kuntal De
- Laetitia H Delmau
- Luke Sadergaski
- Mike Zach
- Padhraic L Mulligan
- Peeyush Nandwana
- Priyanshi Agrawal
- Robert E Norris Jr
- Roger G Miller
- Ryan Dehoff
- Sandra Davern
- Santanu Roy
- Sarah Graham
- Sudarsanam Babu
- Sumit Gupta
- Tomas Grejtak
- Uvinduni Premadasa
- Vera Bocharova
- William Peter
- 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.

Ruthenium is recovered from used nuclear fuel in an oxidizing environment by depositing the volatile RuO4 species onto a polymeric substrate.

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.

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.

Spherical powders applied to nuclear targetry for isotope production will allow for enhanced heat transfer properties, tailored thermal conductivity and minimize time required for target fabrication and post processing.