Six scientists at the Department of Energy’s Oak Ridge National Laboratory were named Battelle Distinguished Inventors, in recognition of obtaining 14 or more patents during their careers at the lab.
Six ORNL scientists have been elected as fellows to the American Association for the Advancement of Science, or AAAS.
ORNL and three partnering institutions have received $4.2 million over three years to apply artificial intelligence to the advancement of complex systems in which human decision making could be enhanced via technology.
ORNL researchers have developed an intelligent power electronic inverter platform that can connect locally sited energy resources such as solar panels, energy storage and electric vehicles and smoothly interact with the utility power grid.
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
For the second year in a row, a team from the Department of Energy’s Oak Ridge and Los Alamos national laboratories led a demonstration hosted by EPB, a community-based utility and telecommunications company serving Chattanooga, Tennessee.
In the race to identify solutions to the COVID-19 pandemic, researchers at the Department of Energy’s Oak Ridge National Laboratory are joining the fight by applying expertise in computational science, advanced manufacturing, data science and neutron science.
As the second-leading cause of death in the United States, cancer is a public health crisis that afflicts nearly one in two people during their lifetime.
The prospect of simulating a fusion plasma is a step closer to reality thanks to a new computational tool developed by scientists in fusion physics, computer science and mathematics at ORNL.
A team of researchers from the Department of Energy’s Oak Ridge National Laboratory has married artificial intelligence and high-performance computing to achieve a peak speed of 20 petaflops in the generation and training of deep learning networks on the