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Media Contacts
Oak Ridge National Laboratory researchers have developed a machine learning model that could help predict the impact pandemics such as COVID-19 have on fuel demand in the United States.
Oak Ridge National Laboratory researchers have built a novel microscope that provides a “chemical lens” for viewing biological systems including cell membranes and biofilms.
Oak Ridge National Laboratory’s high-resolution population distribution database, LandScan USA, became permanently available to researchers in time to aid the response to the novel coronavirus pandemic.
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.
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.
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.
Oak Ridge National Laboratory is training next-generation cameras called dynamic vision sensors, or DVS, to interpret live information—a capability that has applications in robotics and could improve autonomous vehicle sensing.
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
Researchers at Oak Ridge National Laboratory are taking inspiration from neural networks to create computers that mimic the human brain—a quickly growing field known as neuromorphic computing.