Filter Results
Related Organization
- Biological and Environmental Systems Science Directorate (23)
- Computing and Computational Sciences Directorate (35)
- Energy Science and Technology Directorate (217)
- Fusion and Fission Energy and Science Directorate (21)
- Information Technology Services Directorate (2)
- Isotope Science and Enrichment Directorate (6)
- Neutron Sciences Directorate (11)
- Physical Sciences Directorate
(128)
- User Facilities (27)
- (-) National Security Sciences Directorate (17)
Researcher
- Brian Post
- Amit Shyam
- Beth L Armstrong
- Peeyush Nandwana
- Peter Wang
- Alex Plotkowski
- Andrzej Nycz
- Blane Fillingim
- Chris Masuo
- Jun Qu
- Rangasayee Kannan
- Sam Hollifield
- Sudarsanam Babu
- Thomas Feldhausen
- Yong Chae Lim
- Ahmed Hassen
- Chad Steed
- Corson Cramer
- Craig Blue
- J.R. R Matheson
- James A Haynes
- James Klett
- John Lindahl
- Joshua Vaughan
- Junghoon Chae
- Lauren Heinrich
- Meghan Lamm
- Mingyan Li
- Ryan Dehoff
- Steve Bullock
- Sumit Bahl
- Tomas Grejtak
- Travis Humble
- Ying Yang
- Yousub Lee
- Aaron Myers
- Aaron Werth
- Adam Stevens
- Alexander I Wiechert
- Alex Roschli
- Alice Perrin
- Ali Passian
- Andres Marquez Rossy
- Benjamin Manard
- Ben Lamm
- Brian Gibson
- Brian Weber
- Bruce A Pint
- Bryan Lim
- Cameron Adkins
- Charles F Weber
- Charlie Cook
- Christopher Fancher
- Christopher Hershey
- Christopher Ledford
- Chris Tyler
- Costas Tsouris
- Daniel Rasmussen
- David J Mitchell
- David Olvera Trejo
- Dean T Pierce
- Derek Dwyer
- Emilio Piesciorovsky
- Ethan Self
- Eve Tsybina
- Gabriel Veith
- Gary Hahn
- Gerry Knapp
- Glenn R Romanoski
- Gordon Robertson
- Govindarajan Muralidharan
- Harper Jordan
- Isaac Sikkema
- Isha Bhandari
- Jason Jarnagin
- Jay Reynolds
- Jeff Brookins
- Jesse Heineman
- Jiheon Jun
- Joanna Mcfarlane
- Joel Asiamah
- Joel Dawson
- John Potter
- Jonathan Willocks
- Jordan Wright
- Joseph Olatt
- Jovid Rakhmonov
- Justin Cazares
- Kevin Spakes
- Khryslyn G Araño
- Kunal Mondal
- Liam White
- Lilian V Swann
- Louise G Evans
- Luke Koch
- Luke Meyer
- Mahim Mathur
- Mark Provo II
- Marm Dixit
- Mary A Adkisson
- Matthew S Chambers
- Matt Larson
- Matt Vick
- Mengdawn Cheng
- Michael Borish
- Michael Kirka
- Nance Ericson
- Nancy Dudney
- Nicholas Richter
- Oscar Martinez
- Paula Cable-Dunlap
- Priyanshi Agrawal
- Raymond Borges Hink
- Richard L. Reed
- Ritin Mathews
- Rob Root
- Roger G Miller
- Rose Montgomery
- Samudra Dasgupta
- Sarah Graham
- Scott Smith
- Sergiy Kalnaus
- Shajjad Chowdhury
- Srikanth Yoginath
- Steven Guzorek
- Steven J Zinkle
- Sunyong Kwon
- Thomas R Muth
- Tim Graening Seibert
- T Oesch
- Tolga Aytug
- Tony Beard
- Trevor Aguirre
- Vandana Rallabandi
- Varisara Tansakul
- Venugopal K Varma
- Viswadeep Lebakula
- Vlastimil Kunc
- Weicheng Zhong
- Wei Tang
- William Carter
- William Peter
- Xiang Chen
- Yanli Wang
- Yarom Polsky
- Yiyu Wang
- Yukinori Yamamoto
- Yutai Kato
- Zhili Feng

High-gradient magnetic filtration (HGMF) is a non-destructive separation technique that captures magnetic constituents from a matrix containing other non-magnetic species. One characteristic that actinide metals share across much of the group is that they are magnetic.

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 ever-changing cellular communication landscape makes it difficult to identify, map, and localize commercial and private cellular base stations (PCBS).

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 manufacturing method uses multifunctional materials distributed volumetrically to generate a stiffness-based architecture, where continuous surfaces can be created from flat, rapidly produced geometries.

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.

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 QVis Quantum Device Circuit Optimization Module gives users the ability to map a circuit to a specific quantum devices based on the device specifications.

QVis is a visual analytics tool that helps uncover temporal and multivariate variations in noise properties of quantum devices.