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Media Contacts
Ross Wang has been intent on resolving traffic jams since he rode a city bus every day through 40 minutes of traffic to get to his elementary school. That daily journey left an impression that would shape his career.
Scientists at Oak Ridge National Laboratory have developed a solvent that results in a more environmentally friendly process to recover valuable materials from used lithium-ion batteries, supports a stable domestic supply chain for new batteries
A newly released dataset that tracks the movement of everything from food to gasoline across the United States by air, water, truck, rail and pipeline showed the value and tonnage of those goods rose significantly between 2012 and 2017.
Scientists at Oak Ridge National Laboratory have devised a method to identify the unique chemical makeup of every lithium-ion battery around the world, information that could accelerate recycling, recover critical materials and resolve a growing waste stream.
Scientists at Oak Ridge National Laboratory successfully demonstrated a technique to heal dendrites that formed in a solid electrolyte, resolving an issue that can hamper the performance of high energy-density, solid-state batteries.
For a researcher who started out in mechanical engineering with a focus on engine combustion, Martin Wissink has learned a lot about neutrons on the job
Fuel economy can take a tumble when temperatures plummet, according to the Department of Energy’s 2021 Fuel Economy Guide. Compiled by researchers at Oak Ridge National Laboratory, the guide includes several tips to improve a vehicle’s fuel performance.
Algorithms developed at Oak Ridge National Laboratory can greatly enhance X-ray computed tomography images of 3D-printed metal parts, resulting in more accurate, faster scans.
If air taxis become a viable mode of transportation, Oak Ridge National Laboratory researchers have estimated they could reduce fuel consumption significantly while alleviating traffic congestion.
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.