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For nearly three decades, scientists and engineers across the globe have worked on the Square Kilometre Array (SKA), a project focused on designing and building the world’s largest radio telescope. Although the SKA will collect enormous amounts of precise astronomical data in record time, scientific breakthroughs will only be possible with systems able to efficiently process that data.
Researchers at Oak Ridge National Laboratory demonstrated that an additively manufactured polymer layer, when applied to carbon fiber reinforced plastic, or CFRP, can serve as an effective protector against aircraft lightning strikes.
Oak Ridge National Laboratory will give college students the chance to practice cybersecurity skills in a real-world setting as a host of the Department of Energy’s fifth collegiate CyberForce Competition on Nov. 16. The event brings together student teams from across the country to compete at 10 of DOE’s national laboratories.
If humankind reaches Mars this century, an Oak Ridge National Laboratory-developed experiment testing advanced materials for spacecraft may play a key role.
Researchers demonstrated that an additively manufactured hot stamping die can withstand up to 25,000 usage cycles, proving that this technique is a viable solution for production.
Researchers at the Department of Energy’s Oak Ridge National Laboratory have received five 2019 R&D 100 Awards, increasing the lab’s total to 221 since the award’s inception in 1963.
ORNL and The University of Toledo have entered into a memorandum of understanding for collaborative research.
The type of vehicle that will carry people to the Red Planet is shaping up to be “like a two-story house you’re trying to land on another planet.
Three researchers at Oak Ridge National Laboratory will lead or participate in collaborative research projects aimed at harnessing the power of quantum mechanics to advance a range of technologies including computing, fiber optics and network
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.