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Media Contacts
Oak Ridge National Laboratory scientists ingeniously created a sustainable, soft material by combining rubber with woody reinforcements and incorporating “smart” linkages between the components that unlock on demand.
Groundwater withdrawals are expected to peak in about one-third of the world’s basins by 2050, potentially triggering significant trade and agriculture shifts, a new analysis finds.
A team of researchers at ORNL demonstrated that a light-duty passenger electric vehicle can be wirelessly charged at 100-kW with 96% efficiency using polyphase electromagnetic coupling coils with rotating magnetic fields.
To capitalize on AI and researcher strengths, scientists developed a human-AI collaboration recommender system for improved experimentation performance.
Electric vehicles can drive longer distances if their lithium-ion batteries deliver more energy in a lighter package. A prime weight-loss candidate is the current collector, a component that often adds 10% to the weight of a battery cell without contributing energy.
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.
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.
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.
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.