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Media Contacts
Oak Ridge National Laboratory researchers serendipitously discovered when they automated the beam of an electron microscope to precisely drill holes in the atomically thin lattice of graphene, the drilled holes closed up.
Oak Ridge National Laboratory scientists worked with the Colorado School of Mines and Baylor University to develop and test control methods for autonomous water treatment plants that use less energy and generate less waste.
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.
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.
Oak Ridge National Laboratory researchers have built a novel microscope that provides a “chemical lens” for viewing biological systems including cell membranes and biofilms.
An international team of scientists found that rules governing plant growth hold true even at the edges of the world in the Arctic tundra.
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.
To better determine the potential energy cost savings among connected homes, researchers at Oak Ridge National Laboratory developed a computer simulation to more accurately compare energy use on similar weather days.
A team of scientists found that critical interactions between microbes and peat moss break down under warming temperatures, impacting moss health and ultimately carbon stored in soil.
A detailed study by Oak Ridge National Laboratory estimated how much more—or less—energy United States residents might consume by 2050 relative to predicted shifts in seasonal weather patterns