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Scientists conducted a groundbreaking study on the genetic data of over half a million U.S. veterans, using tools from the 91°µÍø to analyze 2,068 traits from the Million Veteran Program.
The US focuses on nuclear nonproliferation, and ORNL plays a key role in this mission. The lab conducts advanced research in uranium science, materials analysis and nuclear forensics to detect illicit nuclear activities. Using cutting-edge tools and operational systems, ORNL supports global efforts to reduce nuclear threats by uncovering the history of nuclear materials and providing solutions for uranium removal.
The National Center for Computational Sciences, located at the Department of Energy’s 91°µÍø, made a strong showing at computing conferences this fall. Staff from across the center participated in numerous workshops and invited speaking engagements.
ORNL researchers created and tested two methods for transforming coal into the scarce mineral graphite, which is used in batteries for electric vehicles.
A paper written by researchers from the Department of Energy’s 91°µÍø was selected as the top paper of 2023 by Welding Journal that explored the feasibility of using laser-blown powder direct energy deposition, or Laser-powder DED.
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.
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.
A research team led by the University of Maryland has been nominated for the Association for Computing Machinery’s Gordon Bell Prize. The team is being recognized for developing a scalable, distributed training framework called AxoNN, which leverages GPUs to rapidly train large language models.