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Phong Le is a computational hydrologist at ORNL who is putting his skills in hydrology, numerical modeling, machine learning and high-performance computing to work quantifying water-related risks for humans and the environment.
FREDA is a new tool being developed at ORNL that will accelerate the design and testing of next-generation fusion devices. It is the first tool of its kind to combine plasma and engineering modeling capabilities and utilize high performance computing resources.
The Department of Energy’s Oak Ridge National Laboratory had a major presence at this year’s International Conference for High Performance Computing, Networking, Storage, and Analysis (SC24).
Joel Brogan, who leads the Multimodal Sensor Analytics group at Oak Ridge National Laboratory, has been elevated to senior membership in the Institute of Electrical and Electronics Engineers.
A chemical reaction can convert two polluting greenhouse gases into valuable building blocks for cleaner fuels and feedstocks, but the high temperature required for the reaction also deactivates the catalyst. A team led by ORNL has found a way to thwart deactivation. The strategy may apply broadly to other catalysts.
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 Oak Ridge National Laboratory 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 Oak Ridge National Laboratory 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.
Plants the world over are absorbing about 31% more carbon dioxide than previously thought. The research, detailed in the journal Nature, is expected to improve Earth system simulations that scientists use to predict the future climate, and spotlights the importance of natural carbon sequestration for greenhouse gas mitigation.