Systems biologist Paul Abraham uses his fascination with proteins, the molecular machines of nature, to explore new ways to engineer more productive ecosystems and hardier bioenergy crops.
The inside of future nuclear fusion energy reactors will be among the harshest environments ever produced on Earth. What’s strong enough to protect the inside of a fusion reactor from plasma-produced heat fluxes akin to space shuttles reentering Earth’s atmosphere?
The Department of Energy has selected Oak Ridge National Laboratory to lead a collaboration charged with developing quantum technologies that will usher in a new era of innovation.
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.
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.
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.