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Critical Materials Institute researchers at Oak Ridge National Laboratory and Arizona State University studied the mineral monazite, an important source of rare-earth elements, to enhance methods of recovering critical materials for energy, defense and manufacturing applications.
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.
Neutron scattering techniques were used as part of a study of a novel nanoreactor material that grows crystalline hydrogen clathrates, or HCs, capable of storing hydrogen.
Researchers at ORNL explored radium’s chemistry to advance cancer treatments using ionizing radiation.
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.
Researchers at Oak Ridge National Laboratory and Momentum Technologies have piloted an industrial-scale process for recycling valuable materials in the millions of tons of e-waste generated annually in the United States.
Researchers at Oak Ridge National Laboratory are using state-of-the-art methods to shed light on chemical separations needed to recover rare-earth elements and secure critical materials for clean energy technologies.
Oak Ridge National Laboratory researchers determined that for every 5 miles per hour that drivers travel over a 50-mph speed limit, fuel economy decreases by 7% and equates to paying an extra 28 cents per gallon at current.
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.