1 - 10 of 13 Results
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.
Efficient thermal management in polymers is essential for developing lightweight, high-strength materials with multifunctional capabilities.
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.
The disclosure is directed to optimized fiber geometries for use in carbon fiber reinforced polymers with increased compressive strength per unit cost. The disclosed fiber geometries reduce the material processing costs as well as increase the compressive strength.
A novel and cost-effective process for the activation of carbon fibers was established.
Contact
To learn more about this technology, email partnerships@ornl.gov or call 865-574-1051.
Neutron scattering experiments cover a large temperature range in which experimenters want to test their samples.
ORNL contributes to developing the concept of passive CO2 DAC by designing and testing a hybrid sorption system. This design aims to leverage the advantages of CO2 solubility and selectivity offered by materials with selective sorption of adsorbents.
Neutron beams are used around the world to study materials for various purposes.
