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
- Alexei P Sokolov
- Anton Ievlev
- Bekki Mills
- Bogdan Dryzhakov
- Bruce Hannan
- John Wenzel
- Keju An
- Kevin M Roccapriore
- Liam Collins
- Loren L Funk
- Mark Loguillo
- Marti Checa Nualart
- Matthew B Stone
- Maxim A Ziatdinov
- Neus Domingo Marimon
- Olga S Ovchinnikova
- Polad Shikhaliev
- Shannon M Mahurin
- Stephen Jesse
- Steven Randolph
- Tao Hong
- Theodore Visscher
- Tomonori Saito
- Victor Fanelli
- Vladislav N Sedov
- Yacouba Diawara
- Yongtao Liu

ORNL has developed a large area thermal neutron detector based on 6LiF/ZnS(Ag) scintillator coupled with wavelength shifting fibers. The detector uses resistive charge divider-based position encoding.

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.

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

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.
