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Mechanism-Based Trait Inference in Plants Using Multiplex Networks, AI Agents, and Translation Tools
This system enables the modular design and optimization of complex plant traits by organizing genes and regulatory mechanisms into interpretable clades.

Mechanism-Based Biological Inference via Multiplex Networks, AI Agents and Cross-Species Translation
This invention provides a platform that uses AI agents and biological networks to uncover and interpret disease-relevant biological mechanisms.

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.

This manufacturing method uses multifunctional materials distributed volumetrically to generate a stiffness-based architecture, where continuous surfaces can be created from flat, rapidly produced geometries.

Through utilizing a two function splice we can increase the splice strength for opposing tows.
Contact:
To learn more about this technology, email partnerships@ornl.gov or call 865-574-1051.

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.