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Researcher
- Venkatakrishnan Singanallur Vaidyanathan
- Amir K Ziabari
- Andrzej Nycz
- Chris Masuo
- Diana E Hun
- Luke Meyer
- Peter Wang
- Philip Bingham
- Philip Boudreaux
- Ryan Dehoff
- Stephen M Killough
- Vincent Paquit
- William Carter
- Alexander I Kolesnikov
- Alexei P Sokolov
- Alex Walters
- Bekki Mills
- Bruce Hannan
- Bryan Maldonado Puente
- Corey Cooke
- Dave Willis
- Gina Accawi
- Gurneesh Jatana
- John Holliman II
- John Wenzel
- Joshua Vaughan
- Keju An
- Loren L Funk
- Luke Chapman
- Mark Loguillo
- Mark M Root
- Matthew B Stone
- Michael Kirka
- Nolan Hayes
- Obaid Rahman
- Polad Shikhaliev
- Ryan Kerekes
- Sally Ghanem
- Shannon M Mahurin
- Sydney Murray III
- Tao Hong
- Theodore Visscher
- Tomonori Saito
- Vasilis Tzoganis
- Vasiliy Morozov
- Victor Fanelli
- Vladislav N Sedov
- Yacouba Diawara
- Yun Liu

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

How fast is a vehicle traveling? For different reasons, this basic question is of interest to other motorists, insurance companies, law enforcement, traffic planners, and security personnel. Solutions to this measurement problem suffer from a number of constraints.

We presented a novel apparatus and method for laser beam position detection and pointing stabilization using analog position-sensitive diodes (PSDs).

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

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.

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

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