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Scientists from Oak Ridge National Laboratory used high-performance computing to create protein models that helped reveal how the outer membrane is tethered to the cell membrane in certain bacteria.
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
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.
Oak Ridge National Laboratory will partner with Cincinnati Children’s Hospital Medical Center to explore ways to deploy expertise in health data science that could more quickly identify patients’ mental health risk factors and aid in
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.
Researchers at Oak Ridge National Laboratory proved that a certain class of ionic liquids, when mixed with commercially available oils, can make gears run more efficiently with less noise and better durability.
In a step toward advancing small modular nuclear reactor designs, scientists at Oak Ridge National Laboratory have run reactor simulations on ORNL supercomputer Summit with greater-than-expected computational efficiency.
Gleaning valuable data from social platforms such as Twitter—particularly to map out critical location information during emergencies— has become more effective and efficient thanks to Oak Ridge National Laboratory.
Oak Ridge National Laboratory scientists have created open source software that scales up analysis of motor designs to run on the fastest computers available, including those accessible to outside users at the Oak Ridge Leadership Computing Facility.
A team of scientists led by Oak Ridge National Laboratory used machine learning methods to generate a high-resolution map of vegetation growing in the remote reaches of the Alaskan tundra.