Katy Bradford: Cassette approach offers compelling construction solution
The Oak Ridge Leadership Computing Facility welcomed users to an interactive meeting at the Department of Energy’s Oak Ridge National Laboratory from Sept. 10–11 for an opportunity to share achievements from the OLCF’s user programs and highlight requirements for the future.
Nuclear physicists at the Department of Energy’s Oak Ridge National Laboratory recently used Frontier, the world’s most powerful supercomputer, to calculate the magnetic properties of calcium-48’s atomic nucleus.
Debjani Singh, a senior scientist at ORNL, leads the HydroSource project, which enhances hydropower research by making water data more accessible and useful. With a background in water resources, data science, and earth science, Singh applies innovative tools like AI to advance research. Her career, shaped by her early exposure to science in India, focuses on bridging research with practical applications.
At ORNL, a group of scientists used neutron scattering techniques to investigate a relatively new functional material called a Weyl semimetal. These Weyl fermions move very quickly in a material and can carry electrical charge at room temperature. Scientists think that Weyl semimetals, if used in future electronics, could allow electricity to flow more efficiently and enable more energy-efficient computers and other electronic devices.
The world’s fastest supercomputer helped researchers simulate synthesizing a material harder and tougher than a diamond — or any other substance on Earth. The study used Frontier to predict the likeliest strategy to synthesize such a material, thought to exist so far only within the interiors of giant exoplanets, or planets beyond our solar system.
The contract will be awarded to develop the newest high-performance computing system at the Oak Ridge Leadership Computing Facility.
To better predict long-term flooding risk, scientists at the Department of Energy’s Oak Ridge National Laboratory developed a 3D modeling framework that captures the complex dynamics of water as it flows across the landscape. The framework seeks to provide valuable insights into which communities are most vulnerable as the climate changes, and was developed for a project that’s assessing climate risk and mitigation pathways for an urban area along the Southeast Texas coast.
ORNL researchers completed successful testing of a gallium nitride transistor for use in more accurate sensors operating near the core of a nuclear reactor. This is an important technical advance particularly for monitoring new, compact.
John Lagergren, a staff scientist in Oak Ridge National Laboratory’s Plant Systems Biology group, is using his expertise in applied math and machine learning to develop neural networks to quickly analyze the vast amounts of data on plant traits amassed at ORNL’s Advanced Plant Phenotyping Laboratory.
A team led by researchers at ORNL explored training strategies for one of the largest artificial intelligence models to date with help from the world’s fastest supercomputer. The findings could help guide training for a new generation of AI models for scientific research.