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Researcher
- Amit Shyam
- Beth L Armstrong
- Peeyush Nandwana
- Alex Plotkowski
- Brian Post
- Joseph Chapman
- Jun Qu
- Nicholas Peters
- Rangasayee Kannan
- Sudarsanam Babu
- Yong Chae Lim
- Blane Fillingim
- Corson Cramer
- Hsuan-Hao Lu
- James A Haynes
- Joseph Lukens
- Lauren Heinrich
- Meghan Lamm
- Muneer Alshowkan
- Ryan Dehoff
- Steve Bullock
- Sumit Bahl
- Thomas Feldhausen
- Tomas Grejtak
- Viswadeep Lebakula
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- Yousub Lee
- Zhili Feng
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- Christopher Ledford
- Clinton Stipek
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- David J Mitchell
- Dean T Pierce
- Debraj De
- Ethan Self
- Eve Tsybina
- Gabriel Veith
- Gautam Malviya Thakur
- Gerry Knapp
- Glenn R Romanoski
- Gordon Robertson
- Govindarajan Muralidharan
- James Gaboardi
- James Klett
- Jay Reynolds
- Jeff Brookins
- Jesse McGaha
- Jessica Moehl
- Jian Chen
- Jiheon Jun
- Jordan Wright
- Jovid Rakhmonov
- Kevin Sparks
- Khryslyn G Araño
- Liz McBride
- Mariam Kiran
- Marm Dixit
- Matthew S Chambers
- Michael Kirka
- Nancy Dudney
- Nicholas Richter
- Peter Wang
- Philipe Ambrozio Dias
- Priyanshi Agrawal
- Roger G Miller
- Rose Montgomery
- Sarah Graham
- Sergiy Kalnaus
- Shajjad Chowdhury
- Steven J Zinkle
- Sunyong Kwon
- Taylor Hauser
- Thomas R Muth
- Tim Graening Seibert
- Todd Thomas
- Tolga Aytug
- Trevor Aguirre
- Venugopal K Varma
- Weicheng Zhong
- Wei Tang
- Wei Zhang
- William Peter
- Xiang Chen
- Xiuling Nie
- Yanli Wang
- Yiyu Wang
- Yukinori Yamamoto
- Yutai Kato

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

Here we present a solution for practically demonstrating path-aware routing and visualizing a self-driving network.

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

Understanding building height is imperative to the overall study of energy efficiency, population distribution, urban morphologies, emergency response, among others. Currently, existing approaches for modelling building height at scale are hindered by two pervasive issues.

Technologies directed to polarization agnostic continuous variable quantum key distribution are described.
Contact:
To learn more about this technology, email partnerships@ornl.gov or call 865-574-1051.

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 development of quantum networking requires architectures capable of dynamically reconfigurable entanglement distribution to meet diverse user needs and ensure tolerance against transmission disruptions.

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.

Polarization drift in quantum networks is a major issue. Fiber transforms a transmitted signal’s polarization differently depending on its environment.

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.