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
- Benjamin Manard
- Kyle Kelley
- Rama K Vasudevan
- Cyril Thompson
- Sergei V Kalinin
- Stephen M Killough
- Alexander I Wiechert
- Anton Ievlev
- Bogdan Dryzhakov
- Bryan Maldonado Puente
- Charles F Weber
- Corey Cooke
- Costas Tsouris
- Diana E Hun
- Joanna Mcfarlane
- Jonathan Willocks
- Kevin M Roccapriore
- Liam Collins
- Marti Checa Nualart
- Matt Vick
- Maxim A Ziatdinov
- Neus Domingo Marimon
- Nolan Hayes
- Olga S Ovchinnikova
- Peter Wang
- Philip Boudreaux
- Ryan Kerekes
- Sally Ghanem
- Stephen Jesse
- Steven Randolph
- Vandana Rallabandi
- Yongtao Liu

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.

The invention introduces a novel, customizable method to create, manipulate, and erase polar topological structures in ferroelectric materials using atomic force microscopy.

High coercive fields prevalent in wurtzite ferroelectrics present a significant challenge, as they hinder efficient polarization switching, which is essential for microelectronic applications.

This invention utilizes new techniques in machine learning to accelerate the training of ML-based communication receivers.

Current technology for heating, ventilation, and air conditioning (HVAC) and other uses such as vending machines rely on refrigerants that have high global warming potential (GWP).

This invention presents technologies for characterizing physical properties of a sample's surface by combining image processing with machine learning techniques.

Technologies for optimizing prefab retrofit panel installation using a real-time evaluator is described.