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Media Contacts
It’s a new type of nuclear reactor core. And the materials that will make it up are novel — products of Oak Ridge National Laboratory’s advanced materials and manufacturing technologies.
A team led by ORNL created a computational model of the proteins responsible for the transformation of mercury to toxic methylmercury, marking a step forward in understanding how the reaction occurs and how mercury cycles through the environment.
As CASL ends and transitions to VERA Users Group, ORNL looks at the history of the program and its impact on the nuclear industry.
Oak Ridge National Laboratory scientists evaluating northern peatland responses to environmental change recorded extraordinary fine-root growth with increasing temperatures, indicating that this previously hidden belowground mechanism may play an important role in how carbon-rich peatlands respond to warming.
Combining expertise in physics, applied math and computing, Oak Ridge National Laboratory scientists are expanding the possibilities for simulating electromagnetic fields that underpin phenomena in materials design and telecommunications.
After its long journey to Mars beginning this summer, NASA’s Perseverance rover will be powered across the planet’s surface in part by plutonium produced at the Department of Energy’s Oak Ridge National Laboratory.
Lithium, the silvery metal that powers smart phones and helps treat bipolar disorders, could also play a significant role in the worldwide effort to harvest on Earth the safe, clean and virtually limitless fusion energy that powers the sun and stars.
Scientists at Oak Ridge National Laboratory have demonstrated a direct relationship between climate warming and carbon loss in a peatland ecosystem.
Scientists at ORNL used neutron scattering and supercomputing to better understand how an organic solvent and water work together to break down plant biomass, creating a pathway to significantly improve the production of renewable
Researchers at Oak Ridge National Laboratory developed a method that uses machine learning to predict seasonal fire risk in Africa, where half of the world’s wildfire-related carbon emissions originate.