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.
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.
In a win for chemistry, inventors at ORNL have designed a closed-loop path for synthesizing an exceptionally tough carbon-fiber-reinforced polymer, or CFRP, and later recovering all of its starting materials.
ORNL climate modeling expertise contributed to a project that assessed global emissions of ammonia from croplands now and in a warmer future, while also identifying solutions tuned to local growing conditions.
New computational framework speeds discovery of fungal metabolites, key to plant health and used in drug therapies and for other uses.
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.
Electric vehicles can drive longer distances if their lithium-ion batteries deliver more energy in a lighter package. A prime weight-loss candidate is the current collector, a component that often adds 10% to the weight of a battery cell without contributing energy.
The 2023 top science achievements from HFIR and SNS feature a broad range of materials research published in high impact journals such as Nature and Advanced Materials.
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%.