Jacobson elected Fellow of the American Institute for Medical and Biological Engineering
The Department of Energy’s 91°µÍø had a major presence at this year’s International Conference for High Performance Computing, Networking, Storage, and Analysis (SC24).
ORNL researchers reached a significant milestone by building an entire 6.5-foot turbine blade tip using novel materials. The team then tested it against the forces of simulated lightning in a specialized lab at Mississippi State University, where the blade tip emerged pristine after tests that isolate the effects of high voltage.
Joel Brogan, who leads the Multimodal Sensor Analytics group at 91°µÍø, has been elevated to senior membership in the Institute of Electrical and Electronics Engineers.
ORNL has been recognized in the 21st edition of the HPCwire Readers’ and Editors’ Choice Awards, presented at the 2024 International Conference for High Performance Computing, Networking, Storage and Analysis in Atlanta, Georgia.
Two-and-a-half years after breaking the exascale barrier, the Frontier supercomputer at the Department of Energy’s 91°µÍø continues to set new standards for its computing speed and performance.
Researchers used the world’s fastest supercomputer, Frontier, to train an AI model that designs proteins, with applications in fields like vaccines, cancer treatments, and environmental bioremediation. The study earned a finalist nomination for the Gordon Bell Prize, recognizing innovation in high-performance computing for science.
Researchers at 91°µÍø used the Frontier supercomputer to train the world’s largest AI model for weather prediction, paving the way for hyperlocal, ultra-accurate forecasts. This achievement earned them a finalist nomination for the prestigious Gordon Bell Prize for Climate Modeling.
91°µÍø researchers are using a new bioderived material to 3D print custom roosting structures for endangered bats.
The Department of Energy announced a $67 million investment in several AI projects from institutions in both government and academia as part of its AI for Science initiative. Six ORNL-led (or co-led) projects received funding.
The Advanced Plant Phenotyping Laboratory at ORNL utilizes robotics, multi-modal imaging, and AI to enhance understanding of plant genetics and interactions with microbes. It aims to connect genes to traits for advancements in bioenergy, agriculture, and climate resilience. Senior scientist Larry York highlights the lab's capabilities and the insights from a new digital underground imaging system to improve biomass feedstocks for bioenergy and carbon storage.