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Researcher
- Venkatakrishnan Singanallur Vaidyanathan
- Adam Willoughby
- Amir K Ziabari
- Diana E Hun
- Eddie Lopez Honorato
- Philip Bingham
- Philip Boudreaux
- Rishi Pillai
- Ryan Dehoff
- Ryan Heldt
- Stephen M Killough
- Tyler Gerczak
- Vincent Paquit
- Brandon Johnston
- Bruce A Pint
- Bryan Maldonado Puente
- Callie Goetz
- Charles Hawkins
- Christopher Hobbs
- Corey Cooke
- Fred List III
- Gina Accawi
- Gurneesh Jatana
- Jiheon Jun
- Keith Carver
- Marie Romedenne
- Mark M Root
- Matt Kurley III
- Michael Kirka
- Nolan Hayes
- Obaid Rahman
- Peter Wang
- Priyanshi Agrawal
- Richard Howard
- Rodney D Hunt
- Ryan Kerekes
- Sally Ghanem
- Thomas Butcher
- Yong Chae Lim
- Zhili Feng

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

A pressure burst feature has been designed and demonstrated for relieving potentially hazardous excess pressure within irradiation capsules used in the ORNL High Flux Isotope Reactor (HFIR).

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

A novel method that prevents detachment of an optical fiber from a metal/alloy tube and allows strain measurement up to higher temperatures, about 800 C has been developed. Standard commercial adhesives typically only survive up to about 400 C.

Sintering additives to improve densification and microstructure control of UN provides a facile approach to producing high quality nuclear fuels.

Test facilities to evaluate materials compatibility in hydrogen are abundant for high pressure and low temperature (<100C).

In order to avoid the limitations and costs due to the use of monolithic components for chemical vapor deposition, we developed a modular system in which the reaction chamber can be composed of a top and bottom cone, nozzle, and in-situ reaction chambers.

This invention utilizes new techniques in machine learning to accelerate the training of ML-based communication receivers.

The technologies provide a coating method to produce corrosion resistant and electrically conductive coating layer on metallic bipolar plates for hydrogen fuel cell and hydrogen electrolyzer applications.

The use of Fluidized Bed Chemical Vapor Deposition to coat particles or fibers is inherently slow and capital intensive, as it requires constant modifications to the equipment to account for changes in the characteristics of the substrates to be coated.