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Media Contacts
While some of her earth system modeling colleagues at ORNL face challenges such as processor allocation or debugging code, Verity Salmon prepares for mosquito swarms and the possibility of grizzly bears.
Ilias Belharouak is leading ORNL’s research efforts in investigating new materials for solid-state batteries, which can double the charging capacity of lithium-ion batteries, commonly used today for electronic devices such as cell phones.
Researchers at ORNL demonstrated that sodium-ion batteries can serve as a low-cost, high performance substitute for rechargeable lithium-ion batteries commonly used in robotics, power tools, and grid-scale energy storage.
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.
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.
Oak Ridge National Laboratory researchers created a geothermal energy storage system that could reduce peak electricity demand up to 37% in homes while helping balance grid operations.
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.
Elizabeth Herndon believes in going the distance whether she is preparing to compete in the 2020 Olympic marathon trials or examining how metals move through the environment as a geochemist at the Department of Energy’s Oak Ridge National Laboratory.
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