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
- Singanallur Venkatakrishnan
- Amir K Ziabari
- Chad Steed
- Junghoon Chae
- Philip Bingham
- Ryan Dehoff
- Travis Humble
- Vincent Paquit
- Aaron Werth
- Ali Passian
- Diana E Hun
- Emilio Piesciorovsky
- Gary Hahn
- Gina Accawi
- Gurneesh Jatana
- Harper Jordan
- Joel Asiamah
- Joel Dawson
- Mark M Root
- Michael Kirka
- Nance Ericson
- Obaid Rahman
- Philip Boudreaux
- Raymond Borges Hink
- Samudra Dasgupta
- Srikanth Yoginath
- Varisara Tansakul
- Yarom Polsky

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

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

The QVis Quantum Device Circuit Optimization Module gives users the ability to map a circuit to a specific quantum devices based on the device specifications.

QVis is a visual analytics tool that helps uncover temporal and multivariate variations in noise properties of quantum devices.

Electrical utility substations are wired with intelligent electronic devices (IEDs), such as protective relays, power meters, and communication switches.

Simurgh revolutionizes industrial CT imaging with AI, enhancing speed and accuracy in nondestructive testing for complex parts, reducing costs.