1 - 10 of 208 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.
The invention teaches a method for separating uranium and the transuranic actinides neptunium, plutonium, and americium from nitric acid solutions by co-crystallization upon lowering the temperature from 60 C to 20 C or lower.
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.
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.
Efficient thermal management in polymers is essential for developing lightweight, high-strength materials with multifunctional capabilities.
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,
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.
Here we present a solution for practically demonstrating path-aware routing and visualizing a self-driving network.