1 - 10 of 70 Results
ORNL researchers have developed a deep learning-based approach to rapidly perform high-quality reconstructions from sparse X-ray computed tomography measurements.
The eDICEML digital twin is proposed which emulates networks and hosts of an instrument-computing ecosystem. It runs natively on an ecosystem’s host or as a portable virtual machine.
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.
How fast is a vehicle traveling? For different reasons, this basic question is of interest to other motorists, insurance companies, law enforcement, traffic planners, and security personnel. Solutions to this measurement problem suffer from a number of constraints.
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.
We have developed a novel extrusion-based 3D printing technique that can achieve a resolution of 0.51 mm layer thickness, and catalyst loading of 44% and 90.5% before and after drying, respectively.
Here we present a solution for practically demonstrating path-aware routing and visualizing a self-driving network.
Enzymes for synthesis of sequenced oligoamide triads and tetrads that can be polymerized into sequenced copolyamides.
Contact
To learn more about this technology, email partnerships@ornl.gov or call 865-574-1051.
We tested 48 diverse homologs of SfaB and identified several enzyme variants that were more active than SfaB at synthesizing the nylon-6,6 monomer.
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.