Filter Results
Related Organization
- Biological and Environmental Systems Science Directorate (29)
- Computing and Computational Sciences Directorate (39)
- Energy Science and Technology Directorate (229)
- Fusion and Fission Energy and Science Directorate (24)
- Isotope Science and Enrichment Directorate (7)
- National Security Sciences Directorate (20)
- Neutron Sciences Directorate (11)
- Physical Sciences Directorate
(138)
- User Facilities (28)
- (-) Information Technology Services Directorate (3)
Researcher
- Peeyush Nandwana
- Amit Shyam
- Blane Fillingim
- Brian Post
- Lauren Heinrich
- Rangasayee Kannan
- Sudarsanam Babu
- Thomas Feldhausen
- Yousub Lee
- Alex Plotkowski
- Andres Marquez Rossy
- Annetta Burger
- Bruce A Pint
- Bryan Lim
- Carter Christopher
- Chance C Brown
- Christopher Fancher
- Dali Wang
- Debraj De
- Gautam Malviya Thakur
- Gordon Robertson
- James Gaboardi
- Jason Jarnagin
- Jay Reynolds
- Jeff Brookins
- Jesse McGaha
- Jian Chen
- Kevin Spakes
- Kevin Sparks
- Lilian V Swann
- Liz McBride
- Mark Provo II
- Peter Wang
- Rob Root
- Ryan Dehoff
- Sam Hollifield
- Steven J Zinkle
- Tim Graening Seibert
- Todd Thomas
- Tomas Grejtak
- Weicheng Zhong
- Wei Tang
- Wei Zhang
- Xiang Chen
- Xiuling Nie
- Yanli Wang
- Ying Yang
- Yiyu Wang
- Yutai Kato
- Zhili Feng

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

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

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.

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.

The first wall and blanket of a fusion energy reactor must maintain structural integrity and performance over long operational periods under neutron irradiation and minimize long-lived radioactive waste.