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
- Kyle Kelley
- Rama K Vasudevan
- Sergei V Kalinin
- Alexander I Kolesnikov
- Anton Ievlev
- Bekki Mills
- Bogdan Dryzhakov
- Brian Sanders
- Jerry Parks
- John Wenzel
- Kevin M Roccapriore
- Liam Collins
- Mark Loguillo
- Marti Checa Nualart
- Matthew B Stone
- Maxim A Ziatdinov
- Neus Domingo Marimon
- Olga S Ovchinnikova
- Stephen Jesse
- Steven Randolph
- Victor Fanelli
- Yongtao Liu

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

Neutron scattering experiments cover a large temperature range in which experimenters want to test their samples.

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

Neutron beams are used around the world to study materials for various purposes.

Direct-acting antivirals are needed to combat coronavirus disease 2019 (COVID-19), which is caused by severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2).

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

There is a critical need for new antiviral drugs for treating infections of severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2).

This invention introduces a system for microscopy called pan-sharpening, enabling the generation of images with both full-spatial and full-spectral resolution without needing to capture the entire dataset, significantly reducing data acquisition time.