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Media Contacts
The Earth System Grid Federation, a multi-agency initiative that gathers and distributes data for top-tier projections of the Earth’s climate, is preparing a series of upgrades.
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.
The Atmospheric Radiation Measurement Data Center is shepherding changes to its operations to make the treasure trove of data more easily available accessible and useful to scientists studying Earth’s climate.
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.
It’s a simple premise: To truly improve the health, safety, and security of human beings, you must first understand where those individuals are.
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.
Researchers at Oak Ridge National Laboratory have empirically quantified the shifts in routine daytime activities, such as getting a morning coffee or takeaway dinner, following safer at home orders during the early days of the COVID-19 pandemic.
An Oak Ridge National Laboratory team developed a novel technique using sensors to monitor seismic and acoustic activity and machine learning to differentiate operational activities at facilities from “noise” in the recorded data.
Oak Ridge National Laboratory is debuting a small satellite ground station that uses high-performance computing to support automated detection of changes to Earth’s landscape.
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.