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Media Contacts
While studying how bio-inspired materials might inform the design of next-generation computers, scientists at ORNL achieved a first-of-its-kind result that could have big implications for both edge computing and human health.
Laboratory Director Thomas Zacharia presented five Director’s Awards during Saturday night's annual Awards Night event hosted by UT-Battelle, which manages ORNL for the Department of Energy.
Marc-Antoni Racing has licensed a collection of patented energy storage technologies developed at ORNL. The technologies focus on components that enable fast-charging, energy-dense batteries for electric and hybrid vehicles and grid storage.
When Hurricane Maria battered Puerto Rico in 2017, winds snapped trees and destroyed homes, while heavy rains transformed streets into rivers. But after the storm passed, the human toll continued to grow as residents struggled without electricity for months. Five years later, power outages remain long and frequent.
A multi-lab research team led by ORNL's Paul Kent is developing a computer application called QMCPACK to enable precise and reliable predictions of the fundamental properties of materials critical in energy research.
Researchers at the Department of Energy’s Oak Ridge National Laboratory and their technologies have received seven 2022 R&D 100 Awards, plus special recognition for a battery-related green technology product.
Doug Kothe has been named associate laboratory director for the Computing and Computational Sciences Directorate at ORNL, effective June 6.
The Frontier supercomputer at the Department of Energy’s Oak Ridge National Laboratory earned the top ranking today as the world’s fastest on the 59th TOP500 list, with 1.1 exaflops of performance. The system is the first to achieve an unprecedented level of computing performance known as exascale, a threshold of a quintillion calculations per second.
Researchers at ORNL are teaching microscopes to drive discoveries with an intuitive algorithm, developed at the lab’s Center for Nanophase Materials Sciences, that could guide breakthroughs in new materials for energy technologies, sensing and computing.
A team of researchers has developed a novel, machine learning–based technique to explore and identify relationships among medical concepts using electronic health record data across multiple healthcare providers.