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Media Contacts
New polymer materials under development at Oak Ridge National Laboratory could enable safer, more stable batteries needed for electric vehicles and grid energy storage.
Researchers at Oak Ridge National Laboratory and Korea’s Sungkyunkwan University are using advanced microscopy to nanoengineer promising materials for computing and electronics in a beyond-Moore era.
Oak Ridge National Laboratory researchers developed an invertible neural network, a type of artificial intelligence that mimics the human brain, to improve accuracy in climate-change models and predictions.
Researchers at Oak Ridge National Laboratory have empirically quantified the shifts in routine daytime activities, such as getting a morning coffee or takeaway dinner, following safer at home orders during the early days of the COVID-19 pandemic.
An Oak Ridge National Laboratory team developed a novel technique using sensors to monitor seismic and acoustic activity and machine learning to differentiate operational activities at facilities from “noise” in the recorded data.
Oak Ridge National Laboratory is debuting a small satellite ground station that uses high-performance computing to support automated detection of changes to Earth’s landscape.
Oak Ridge National Laboratory researchers demonstrated an electron microscopy technique for imaging lithium in energy storage materials, such as lithium ion batteries, at the atomic scale.
Oak Ridge National Laboratory researchers collaborated with Iowa State University and RJ Lee Group to demonstrate a safe and effective antiviral coating for N95 masks. The coating destroys the COVID-19-causing coronavirus and could enable reuse of masks made from various fabrics.
University of Pennsylvania researchers called on computational systems biology expertise at Oak Ridge National Laboratory to analyze large datasets of single-cell RNA sequencing from skin samples afflicted with atopic dermatitis.
Oak Ridge National Laboratory scientists worked with the Colorado School of Mines and Baylor University to develop and test control methods for autonomous water treatment plants that use less energy and generate less waste.