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The ForWarn visualization tool was co-developed by ORNL with the U.S. Forest Service. The tool captures and analyzes satellite imagery to track impacts such as storms, wildfire and pests on forests across the nation.

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.

Researchers have identified a molecule essential for the microbial conversion of inorganic mercury into the neurotoxin methylmercury, moving closer to blocking the dangerous pollutant before it forms.

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.

Oak Ridge National Laboratory researchers are using a new bioderived material to 3D print custom roosting structures for endangered bats.

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.

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.