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Researcher
- Vivek Sujan
- Alex Plotkowski
- Amit Shyam
- Omer Onar
- Ryan Dehoff
- Singanallur Venkatakrishnan
- Adam Siekmann
- Amir K Ziabari
- Diana E Hun
- Erdem Asa
- James A Haynes
- Philip Bingham
- Philip Boudreaux
- Stephen M Killough
- Subho Mukherjee
- Sumit Bahl
- Vincent Paquit
- Alice Perrin
- Andres Marquez Rossy
- Bryan Maldonado Puente
- Corey Cooke
- Gerry Knapp
- Gina Accawi
- Gurneesh Jatana
- Hyeonsup Lim
- Isabelle Snyder
- Jovid Rakhmonov
- Mark M Root
- Michael Kirka
- Nicholas Richter
- Nolan Hayes
- Obaid Rahman
- Peeyush Nandwana
- Peter Wang
- Ryan Kerekes
- Sally Ghanem
- Shajjad Chowdhury
- Sunyong Kwon
- Ying Yang

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

Currently available cast Al alloys are not suitable for various high-performance conductor applications, such as rotor, inverter, windings, busbar, heat exchangers/sinks, etc.

The invented alloys are a new family of Al-Mg alloys. This new family of Al-based alloys demonstrate an excellent ductility (10 ± 2 % elongation) despite the high content of impurities commonly observed in recycled aluminum.

The growing demand for electric vehicles (EVs) has necessitated significant advancements in EV charging technologies to ensure efficient and reliable operation.

The growing demand for renewable energy sources has propelled the development of advanced power conversion systems, particularly in applications involving fuel cells.

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

This invention presents a multiport converter (MPC) based power supply to charge the 12 V and 24 V auxiliary batteries in heavy duty (HD) fuel cell (FC) electric vehicle (EV) power train.

This invention presents an integrated strategy to reduce end-user electricity costs and grid carbon emissions by efficiently utilizing Distributed Energy Resources (DER) and grid-scale electrical energy storage systems, such as batteries.

No readily available public data exists for vehicle class and weight information that covers the entire U.S. highway network. The Travel Monitoring Analysis System, managed by the Federal Highway Administration covers only less than 1% of the US highway network.