Artificial intelligence tools secure tomorrow’s electric grid
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.
A team from the ORNL has conducted a series of experiments to gain a better understanding of quantum mechanics and pursue advances in quantum networking and quantum computing, which could lead to practical applications in cybersecurity and other areas.
Nuclear scientists at Oak Ridge National Laboratory have established a Nuclear Quality Assurance-1 program for a software product designed to simulate today’s commercial nuclear reactors – removing a significant barrier for industry adoption of the technology.
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 across the scientific spectrum crave data, as it is essential to understanding the natural world and, by extension, accelerating scientific progress.
Thought leaders from across the maritime community came together at Oak Ridge National Laboratory to explore the emerging new energy landscape for the maritime transportation system during the Ninth Annual Maritime Risk Symposium.
Carbon fiber composites—lightweight and strong—are great structural materials for automobiles, aircraft and other transportation vehicles. They consist of a polymer matrix, such as epoxy, into which reinforcing carbon fibers have been embedded. Because of differences in the mecha...
As Puerto Rico works to restore and modernize its power grid after last year’s devastating hurricane season, researchers at Oak Ridge National Laboratory have stepped up to provide unique analysis, sensing and modeling tools to better inform decisions.
Self-driving cars promise to keep traffic moving smoothly and reduce fuel usage, but proving those advantages has been a challenge with so few connected and automated vehicles, or CAVs, currently on the road.