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Media Contacts
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.
Oak Ridge National Laboratory scientists evaluating northern peatland responses to environmental change recorded extraordinary fine-root growth with increasing temperatures, indicating that this previously hidden belowground mechanism may play an important role in how carbon-rich peatlands respond to warming.
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.
A multi-institutional research team found that changing environmental conditions are affecting forests around the globe, leading to increasing tree death and uncertainty about the ability of forests to recover.
Oak Ridge National Laboratory researchers have discovered a better way to separate actinium-227, a rare isotope essential for an FDA-approved cancer treatment.
Scientists have tapped the immense power of the Summit supercomputer at Oak Ridge National Laboratory to comb through millions of medical journal articles to identify potential vaccines, drugs and effective measures that could suppress or stop the
An international team of scientists found that rules governing plant growth hold true even at the edges of the world in the Arctic tundra.
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 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.
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.