Researchers from Oak Ridge National Laboratory and Northeastern University modeled how extreme conditions in a changing climate affect the land’s ability to absorb atmospheric carbon — a key process for mitigating human-caused emissions. They found that 88% of Earth’s regions could become carbon emitters by the end of the 21st century.
Stephen Dahunsi’s desire to see more countries safely deploy nuclear energy is personal. Growing up in Nigeria, he routinely witnessed prolonged electricity blackouts as a result of unreliable energy supplies. It’s a problem he hopes future generations won’t have to experience.
A study by Oak Ridge National Laboratory researchers has demonstrated how satellites could enable more efficient, secure quantum networks.
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.
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.
Cameras see the world differently than humans. Resolution, equipment, lighting, distance and atmospheric conditions can impact how a person interprets objects on a photo.
As scientists study approaches to best sustain a fusion reactor, a team led by Oak Ridge National Laboratory investigated injecting shattered argon pellets into a super-hot plasma, when needed, to protect the reactor’s interior wall from high-energy runaway electrons.
If humankind reaches Mars this century, an Oak Ridge National Laboratory-developed experiment testing advanced materials for spacecraft may play a key role.
Jason Nattress, an Alvin M. Weinberg Fellow at the Department of Energy’s Oak Ridge National Laboratory, found his calling on a nuclear submarine.
In collaboration with the Department of Veterans Affairs, a team at Oak Ridge National Laboratory has expanded a VA-developed predictive computing model to identify veterans at risk of suicide and sped it up to run 300 times faster, a gain that could profoundly affect the VA’s ability to reach susceptible veterans quickly.