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Researcher
- Singanallur Venkatakrishnan
- Ali Riza Ekti
- Amir K Ziabari
- Hongbin Sun
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- Pradeep Ramuhalli
- Praveen Cheekatamarla
- Ruhul Amin
- Sam Hollifield
- Vishaldeep Sharma
- Vittorio Badalassi
- Yarom Polsky

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

This technology can help to increase number of application areas of Wireless Power Transfer systems. It can be applied to consumer electronics, defense industry, automotive industry etc.

The invention presented here addresses key challenges associated with counterfeit refrigerants by ensuring safety, maintaining system performance, supporting environmental compliance, and mitigating health and legal risks.

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

Faults in the power grid cause many problems that can result in catastrophic failures. Real-time fault detection in the power grid system is crucial to sustain the power systems' reliability, stability, and quality.

A novel approach is presented herein to improve time to onset of natural convection stemming from fuel element porosity during a failure mode of a nuclear reactor.

Recent advances in magnetic fusion (tokamak) technology have attracted billions of dollars of investments in startups from venture capitals and corporations to develop devices demonstrating net energy gain in a self-heated burning plasma, such as SPARC (under construction) and

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