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Researcher
- Alex Plotkowski
- Amit Shyam
- Yong Chae Lim
- Zhili Feng
- James A Haynes
- Jian Chen
- Mike Zach
- Peeyush Nandwana
- Rangasayee Kannan
- Ryan Dehoff
- Sumit Bahl
- Wei Zhang
- Adam Stevens
- Alice Perrin
- Andres Marquez Rossy
- Andrew F May
- Annetta Burger
- Ben Garrison
- Brad Johnson
- Brian Post
- Bruce Moyer
- Bryan Lim
- Carter Christopher
- Chance C Brown
- Charlie Cook
- Christopher Hershey
- Craig Blue
- Dali Wang
- Daniel Rasmussen
- Debjani Pal
- Debraj De
- Gautam Malviya Thakur
- Gerry Knapp
- Hsin Wang
- James Gaboardi
- James Klett
- Jeffrey Einkauf
- Jennifer M Pyles
- Jesse McGaha
- Jiheon Jun
- John Lindahl
- Jovid Rakhmonov
- Justin Griswold
- Kevin Sparks
- Kuntal De
- Laetitia H Delmau
- Liz McBride
- Luke Sadergaski
- Nedim Cinbiz
- Nicholas Richter
- Padhraic L Mulligan
- Priyanshi Agrawal
- Roger G Miller
- Sandra Davern
- Sarah Graham
- Sudarsanam Babu
- Sunyong Kwon
- Todd Thomas
- Tomas Grejtak
- Tony Beard
- William Peter
- Xiuling Nie
- Ying Yang
- Yiyu Wang
- Yukinori Yamamoto

Often there are major challenges in developing diverse and complex human mobility metrics systematically and quickly.

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.

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.

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.

The technologies provide a system and method of needling of veiled AS4 fabric tape.

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.

ORNL will develop an advanced high-performing RTG using a novel radioisotope heat source.