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Media Contacts
Researchers at Oak Ridge National Laboratory have designed architecture, software and control strategies for a futuristic EV truck stop that can draw megawatts of power and reduce carbon emissions.
A multi-lab research team led by ORNL's Paul Kent is developing a computer application called QMCPACK to enable precise and reliable predictions of the fundamental properties of materials critical in energy research.
To further the potential benefits of the nation’s hydropower resources, researchers at Oak Ridge National Laboratory have developed and maintain a comprehensive water energy digital platform called HydroSource.
Scientists are using Oak Ridge National Laboratory’s Multicharged Ion Research Facility to simulate the cosmic origin of X-ray emissions resulting when highly charged ions collide with neutral atoms and molecules, such as helium and gaseous hydrogen.
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.
A new Department of Energy report produced by Oak Ridge National Laboratory identifies several supply chain must-haves in maintaining the pivotal role hydropower will play in decarbonizing the nation’s grid.
Measuring water quality throughout river networks with precision, speed and at lower cost than traditional methods is now possible with AquaBOT, an aquatic drone developed by Oak Ridge National Laboratory.
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.