Oak Ridge National Laboratory scientists seeking the source of charge loss in lithium-ion batteries demonstrated that coupling a thin-film cathode with a solid electrolyte is a rapid way to determine the root cause.
In the search to create materials that can withstand extreme radiation, Yanwen Zhang, a researcher at the Department of Energy’s Oak Ridge National Laboratory, says that materials scientists must think outside the box.
Scientists have tapped the immense power of the Summit supercomputer at Oak Ridge National Laboratory to comb through millions of medical journal articles to identify potential vaccines, drugs and effective measures that could suppress or stop the
Oak Ridge National Laboratory researchers have developed a thin film, highly conductive solid-state electrolyte made of a polymer and ceramic-based composite for lithium metal batteries.
In the Physics Division of the Department of Energy’s Oak Ridge National Laboratory, James (“Mitch”) Allmond conducts experiments and uses theoretical models to advance our understanding of the structure of atomic nuclei, which are made of various combinations of protons and neutrons (nucleons).
As a teenager, Kat Royston had a lot of questions. Then an advanced-placement class in physics convinced her all the answers were out there.
Scientists at Oak Ridge National Laboratory used a focused beam of electrons to stitch platinum-silicon molecules into graphene, marking the first deliberate insertion of artificial molecules into a graphene host matrix.
A novel approach developed by scientists at ORNL can scan massive datasets of large-scale satellite images to more accurately map infrastructure – such as buildings and roads – in hours versus days.
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.
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.