Oak Ridge National Laboratory researchers have developed a machine learning model that could help predict the impact pandemics such as COVID-19 have on fuel demand in the United States.
Researchers at Oak Ridge National Laboratory developed a method that uses machine learning to predict seasonal fire risk in Africa, where half of the world’s wildfire-related carbon emissions originate.
Oak Ridge National Laboratory researchers have developed a thin film, highly conductive solid-state electrolyte made of a polymer and ceramic-based composite for lithium metal batteries.
Researchers at Oak Ridge National Laboratory demonstrated a 20-kilowatt bi-directional wireless charging system on a UPS plug-in hybrid electric delivery truck, advancing the technology to a larger class of vehicles and enabling a new energy storage method for fleet owners and their facilities.
A novel approach developed by scientists at ORNL can scan massive datasets of large-scale satellite images to more accurately map infrastructure – such as buildings and roads – in hours versus days.
Researchers at ORNL demonstrated that sodium-ion batteries can serve as a low-cost, high performance substitute for rechargeable lithium-ion batteries commonly used in robotics, power tools, and grid-scale energy storage.
Oak Ridge National Laboratory researchers created a geothermal energy storage system that could reduce peak electricity demand up to 37% in homes while helping balance grid operations.
To better determine the potential energy cost savings among connected homes, researchers at Oak Ridge National Laboratory developed a computer simulation to more accurately compare energy use on similar weather days.
A detailed study by Oak Ridge National Laboratory estimated how much more—or less—energy United States residents might consume by 2050 relative to predicted shifts in seasonal weather patterns