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Researcher
- Joseph Chapman
- Nicholas Peters
- Srikanth Yoginath
- Hongbin Sun
- Hsuan-Hao Lu
- James J Nutaro
- Joseph Lukens
- Muneer Alshowkan
- Prashant Jain
- Pratishtha Shukla
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- Anees Alnajjar
- Brian Williams
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- Harper Jordan
- Ian Greenquist
- Ilias Belharouak
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- Joel Dawson
- Mariam Kiran
- Nance Ericson
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- Pablo Moriano Salazar
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- Pradeep Ramuhalli
- Praveen Cheekatamarla
- Rangasayee Kannan
- Ruhul Amin
- Tomas Grejtak
- Varisara Tansakul
- Vishaldeep Sharma
- Vittorio Badalassi
- Yiyu Wang

Here we present a solution for practically demonstrating path-aware routing and visualizing a self-driving network.

Technologies directed to polarization agnostic continuous variable quantum key distribution are described.
Contact:
To learn more about this technology, email partnerships@ornl.gov or call 865-574-1051.

The development of quantum networking requires architectures capable of dynamically reconfigurable entanglement distribution to meet diverse user needs and ensure tolerance against transmission disruptions.

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.

Polarization drift in quantum networks is a major issue. Fiber transforms a transmitted signal’s polarization differently depending on its environment.

This invention addresses a key challenge in quantum communication networks by developing a controlled-NOT (CNOT) gate that operates between two degrees of freedom (DoFs) within a single photon: polarization and frequency.

A new nanostructured bainitic steel with accelerated kinetics for bainite formation at 200 C was designed using a coupled CALPHAD, machine learning, and data mining approach.

Polarization drift in quantum networks is a major issue. Fiber transforms a transmitted signal’s polarization differently depending on its environment.

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.

Digital twins (DTs) have emerged as essential tools for monitoring, predicting, and optimizing physical systems by using real-time data.