1 - 10 of 145 Results
ORNL researchers have developed a deep learning-based approach to rapidly perform high-quality reconstructions from sparse X-ray computed tomography measurements.
The technology will offer supportless DIW of complex structures using vinyl ester resin, facilitated by multidirectional 6 axis printing.
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.
The present invention is a carbon nanofiber composite for use as the cathode matrix in an alkali-metal polysulfide flow battery. The CNF composite demonstrates an improvement in sulfur utilization compared to carbon paper alone.
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.
Process to coat air and or moisture sensitive solid electrolytes for all solid state batteries.
Contact
To learn more about this technology, email partnerships@ornl.gov or call 865-574-1051.
This invention utilizes a custom-synthesized vinyl trifluoromethanesulfonimide (VTFSI) salt and an alcohol containing small molecule or polymer for the synthesis of novel single-ion conducting polymer electrolytes for the use in Li-ion and beyond Li-ion batteries, fuel cells,
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.