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Chad Parish, a senior researcher at ORNL, studies materials at the atomic level to improve nuclear reactors. His work focuses on fusion and fission energy, using microscopy and collaborating with experts to advance materials for extreme environments.

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.

Scientists and land managers interested in accessing the first dataset of its kind on one of the most biologically diverse ecosystems in the world were given hands-on tutorials during a recent workshop by researchers supporting the ORNL Distributed Active Archive Center for Biogeochemical Dynamics.


Scientists at the Department of Energy’s 91°µÍø recently demonstrated an autonomous robotic field monitoring, sampling and data-gathering system that could accelerate understanding of interactions among plants, soil and the environment.

In early November, researchers at the Department of Energy’s Argonne National Laboratory used the fastest supercomputer on the planet to run the largest astrophysical simulation of the universe ever conducted. The achievement was made using the Frontier supercomputer at 91°µÍø.

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 multi-institutional team of researchers led by the King Abdullah University of Science and Technology, or KAUST, Saudi Arabia, has been nominated for the Association for Computing Machinery’s 2024 Gordon Bell Prize for Climate Modelling.