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
- Adam M Guss
- Ali Passian
- Joseph Chapman
- Nicholas Peters
- Singanallur Venkatakrishnan
- Vincent Paquit
- Amir K Ziabari
- Andrzej Nycz
- Diana E Hun
- Hsuan-Hao Lu
- Joseph Lukens
- Josh Michener
- Kuntal De
- Muneer Alshowkan
- Philip Bingham
- Philip Boudreaux
- Ryan Dehoff
- Stephen M Killough
- Udaya C Kalluri
- Xiaohan Yang
- Alex Walters
- Anees Alnajjar
- Austin Carroll
- Biruk A Feyissa
- Brian Williams
- Bryan Maldonado Puente
- Carrie Eckert
- Chris Masuo
- Claire Marvinney
- Clay Leach
- Corey Cooke
- Debjani Pal
- Gerald Tuskan
- Gina Accawi
- Gurneesh Jatana
- Harper Jordan
- Ilenne Del Valle Kessra
- Isaiah Dishner
- Jay D Huenemann
- Jeff Foster
- Joanna Tannous
- Joel Asiamah
- Joel Dawson
- John F Cahill
- Kyle Davis
- Liangyu Qian
- Mariam Kiran
- Mark M Root
- Michael Kirka
- Nance Ericson
- Nolan Hayes
- Obaid Rahman
- Paul Abraham
- Peter Wang
- Ryan Kerekes
- Sally Ghanem
- Serena Chen
- Srikanth Yoginath
- Varisara Tansakul
- Vilmos Kertesz
- Yang Liu

ORNL researchers have developed a deep learning-based approach to rapidly perform high-quality reconstructions from sparse X-ray computed tomography measurements.

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

Technologies directed to polarization agnostic continuous variable quantum key distribution are described.
Contact:
To learn more about this technology, email partnerships@ornl.gov or call 865-574-1051.

By engineering the Serine Integrase Assisted Genome Engineering (SAGE) genetic toolkit in an industrial strain of Aspergillus niger, we have established its proof of principle for applicability in Eukaryotes.

The development of quantum networking requires architectures capable of dynamically reconfigurable entanglement distribution to meet diverse user needs and ensure tolerance against transmission disruptions.

We have been working to adapt background oriented schlieren (BOS) imaging to directly visualize building leakage, which is fast and easy.

Polarization drift in quantum networks is a major issue. Fiber transforms a transmitted signal’s polarization differently depending on its environment.

This invention addresses a key challenge in quantum communication networks by developing a controlled-NOT (CNOT) gate that operates between two degrees of freedom (DoFs) within a single photon: polarization and frequency.