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)
- National Security Sciences Directorate (17)
- Neutron Sciences Directorate (11)
- Physical Sciences Directorate (128)
- User Facilities (27)
Researcher
- Andrzej Nycz
- Chris Masuo
- Amit Shyam
- Peter Wang
- Alex Plotkowski
- Alex Walters
- Srikanth Yoginath
- Anees Alnajjar
- Brian Gibson
- James A Haynes
- James J Nutaro
- Joshua Vaughan
- Luke Meyer
- Pratishtha Shukla
- Sergiy Kalnaus
- Sudip Seal
- Sumit Bahl
- Udaya C Kalluri
- William Carter
- Akash Jag Prasad
- Alice Perrin
- Ali Passian
- Andres Marquez Rossy
- Beth L Armstrong
- Calen Kimmell
- Chelo Chavez
- Christopher Fancher
- Chris Tyler
- Clay Leach
- Craig A Bridges
- Georgios Polyzos
- Gerry Knapp
- Gordon Robertson
- Harper Jordan
- J.R. R Matheson
- Jaswinder Sharma
- Jaydeep Karandikar
- Jay Reynolds
- Jeff Brookins
- Jesse Heineman
- Joel Asiamah
- Joel Dawson
- John Potter
- Jovid Rakhmonov
- Mariam Kiran
- Nageswara Rao
- Nance Ericson
- Nancy Dudney
- Nicholas Richter
- Pablo Moriano Salazar
- Peeyush Nandwana
- Riley Wallace
- Ritin Mathews
- Ryan Dehoff
- Sheng Dai
- Sunyong Kwon
- Varisara Tansakul
- Vincent Paquit
- Vladimir Orlyanchik
- Xiaohan Yang
- Ying Yang

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

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.

System and method for part porosity monitoring of additively manufactured components using machining
In additive manufacturing, choice of process parameters for a given material and geometry can result in porosities in the build volume, which can result in scrap.

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.

We developed and incorporated two innovative mPET/Cu and mPET/Al foils as current collectors in LIBs to enhance cell energy density under XFC conditions.

Digital twins (DTs) have emerged as essential tools for monitoring, predicting, and optimizing physical systems by using real-time data.

Simulation cloning is a technique in which dynamically cloned simulations’ state spaces differ from their parent simulation due to intervening events.

We present the design, assembly and demonstration of functionality for a new custom integrated robotics-based automated soil sampling technology as part of a larger vision for future edge computing- and AI- enabled bioenergy field monitoring and management technologies called

Creating a framework (method) for bots (agents) to autonomously, in real time, dynamically divide and execute a complex manufacturing (or any suitable) task in a collaborative, parallel-sequential way without required human interaction.