Kate Evans, director for the Computational Sciences and Engineering Division at ORNL, has been awarded the 2024 Society for Industrial and Applied Mathematicians Activity Group on Mathematics of Planet Earth Prize.
Anuj J. Kapadia, who heads the Advanced Computing Methods for Health Sciences Section at ORNL, has been elected as president of the Southeastern Chapter of the American Association of Physicists in Medicine.
Chelsea Chen, a polymer physicist at ORNL, is studying ion transport in solid electrolytes that could help electric vehicle battery charges last longer.
Pablo Moriano, a research scientist in the Computer Science and Mathematics Division at ORNL, was selected as a member of the 2024 Class of MGB-SIAM Early Career Fellows.
Researchers at the Statewide California Earthquake Center are unraveling the mysteries of earthquakes by using physics-based computational models running on high-performance computing systems at ORNL. The team’s findings will provide a better understanding of seismic hazards in the Golden State.
New computational framework speeds discovery of fungal metabolites, key to plant health and used in drug therapies and for other uses.
Corning uses neutron scattering to study the stability of different types of glass. Recently, researchers for the company have found that understanding the stability of the rings of atoms in glass materials can help predict the performance of glass products.
In summer 2023, ORNL's Prasanna Balaprakash was invited to speak at a roundtable discussion focused on the importance of academic artificial intelligence research and development hosted by the White House Office of Science and Technology Policy and the U.S. National Science Foundation.
The U.S. Department of Energy’s Oak Ridge Leadership Computing Facility has informed the recipients of high-performance computing time through the SummitPLUS allocation program, which extends the operation of the Summit supercomputer through October 2024.
A team from DOE’s Oak Ridge, Los Alamos and Sandia National Laboratories has developed a new solver algorithm that reduces the total run time of the Model for Prediction Across Scales-Ocean, or MPAS-Ocean, E3SM’s ocean circulation model, by 45%.