1 - 10 of 11 Results
ORNL researchers have developed a deep learning-based approach to rapidly perform high-quality reconstructions from sparse X-ray computed tomography measurements.
We have been working to adapt background oriented schlieren (BOS) imaging to directly visualize building leakage, which is fast and easy.
The invention introduces a novel, customizable method to create, manipulate, and erase polar topological structures in ferroelectric materials using atomic force microscopy.
High coercive fields prevalent in wurtzite ferroelectrics present a significant challenge, as they hinder efficient polarization switching, which is essential for microelectronic applications.
Measurements of grid voltage and current are essential for the optimal operation of the grid protection and control (P&C) systems.
Multi-terminal DC (MTdc) systems based on high-voltage DC (HVDC) transmission technology is an upcoming concept. In such systems, either asymmetric monopole or bi-pole systems are generally employed. Such systems are not suitable for easy expansion.
Stability performance of interconnected power grids plays crucial roles on their secure operation to prevent cascading failure and blackout.
Technologies directed to a multi-port autonomous reconfigurable solar power plant are described.
This invention presents technologies for characterizing physical properties of a sample's surface by combining image processing with machine learning techniques.
Simurgh revolutionizes industrial CT imaging with AI, enhancing speed and accuracy in nondestructive testing for complex parts, reducing costs.