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.
An advance in a topological insulator material — whose interior behaves like an electrical insulator but whose surface behaves like a conductor — could revolutionize the fields of next-generation electronics and quantum computing, according to scientists at ORNL.
A study led by Oak Ridge National Laboratory researchers identifies a new potential application in quantum computing that could be part of the next computational revolution.
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.
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.
The presence of minerals called ash in plants makes little difference to the fitness of new naturally derived compound materials designed for additive manufacturing, an Oak Ridge National Laboratory-led team found.
ORNL researchers discovered genetic mutations that underlie autism using a new approach that could lead to better diagnostics and drug therapies.
Global carbon emissions from inland waters such as lakes, rivers, streams and ponds are being undercounted by about 13% and will likely continue to rise given climate events and land use changes, ORNL scientists found.
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.