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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.
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.
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.
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.
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.