In the search for ways to fight methylmercury in global waterways, scientists at Oak Ridge National Laboratory discovered that some forms of phytoplankton are good at degrading the potent neurotoxin.
Oak Ridge National Laboratory scientists exploring bioenergy plant genetics have made a surprising discovery: a protein domain that could lead to new COVID-19 treatments.
Warming a crystal of the mineral fresnoite, ORNL scientists discovered that excitations called phasons carried heat three times farther and faster than phonons, the excitations that usually carry heat through a material.
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.
Researchers at Oak Ridge National Laboratory demonstrated that an additively manufactured polymer layer, when applied to carbon fiber reinforced plastic, or CFRP, can serve as an effective protector against aircraft lightning strikes.
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.
In a recent study, researchers at Oak Ridge National Laboratory performed experiments in a prototype fusion reactor materials testing facility to develop a method that uses microwaves to raise the plasma’s temperature closer to the extreme values
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.