Researchers from Yale University and ORNL collaborated on neutron scattering experiments to study hydrogen atom locations and their effects on iron in a compound similar to those commonly used in industrial catalysts.
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.
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.
ORNL researchers discovered genetic mutations that underlie autism using a new approach that could lead to better diagnostics and drug therapies.
Neutron scattering techniques were used as part of a study of a novel nanoreactor material that grows crystalline hydrogen clathrates, or HCs, capable of storing hydrogen.
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.
Oak Ridge National Laboratory researchers developed an invertible neural network, a type of artificial intelligence that mimics the human brain, to improve accuracy in climate-change models and predictions.
An Oak Ridge National Laboratory team developed a novel technique using sensors to monitor seismic and acoustic activity and machine learning to differentiate operational activities at facilities from “noise” in the recorded data.
Textile engineering researchers from North Carolina State University used neutrons at Oak Ridge National Laboratory to identify a special wicking mechanism in a type of cotton yarn that allows the fibers to control the flow of liquid across certain strands.
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.