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Measurements of grid voltage and current are essential for the optimal operation of the grid protection and control (P&C) systems.
Hydrogen is in great demand, but production relies heavily on hydrocarbons utilization. This process contributes greenhouse gases release into the atmosphere.
Scanning transmission electron microscopes are useful for a variety of applications. Atomic defects in materials are critical for areas such as quantum photonics, magnetic storage, and catalysis.
Water heaters and heating, ventilation, and air conditioning (HVAC) systems collectively consume about 58% of home energy use.
This invention disclosure proposes a novel method for signal detection and feature extraction based on the spectral correlation function, enabling improved characterization of grid-signal distortions.
An ORNL invention proposes using 3D printing to make conductors with space-filling thin-wall cross sections. Space-filling thin-wall profiles will maximize the conductor volume while restricting the path for eddy currents induction.
This technology overcomes the limitations of carbon materials like Carbon Nanotubes (CNT) and graphene in carbon dioxide reduction. These materials show significant inactivity in electrochemical carbon dioxide (Na-CO2)reduction applications.
A human-in-the-loop machine learning (hML) technology potentially enhances experimental workflows by integrating human expertise with AI automation.
The invention is related to the implementation of an bi-directional and isolated electric vehicle charger. The bidirectionality allows the electric vehicles to support the grid in case of disturbances thereby reducing the stress on the existing infrastructure.
The scanning transmission electron microscope (STEM) provides unprecedented spatial resolution and is critical for many applications, primarily for imaging matter at the atomic and nanoscales and obtaining spectroscopic information at similar length scales.