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.
ORNL researchers have developed an intelligent power electronic inverter platform that can connect locally sited energy resources such as solar panels, energy storage and electric vehicles and smoothly interact with the utility power grid.
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.
The Department of Energy’s Office of Science has selected three Oak Ridge National Laboratory scientists for Early Career Research Program awards.
Researchers at the Department of Energy’s Oak Ridge National Laboratory are refining their design of a 3D-printed nuclear reactor core, scaling up the additive manufacturing process necessary to build it, and developing methods
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.
Researchers at the Department of Energy’s Oak Ridge National Laboratory (ORNL) in late February demonstrated a 20-kilowatt bi-directional wireless charging system installed on a UPS medium-duty, plug-in hybrid electric delivery truck.
Each year, approximately 6 billion gallons of fuel are wasted as vehicles wait at stop lights or sit in dense traffic with engines idling, according to US Department of Energy estimates.
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.
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.