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Media Contacts
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.
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.
Scientists at the Department of Energy’s Oak Ridge National Laboratory are using a new modeling framework in conjunction with data collected from marshes in the Mississippi Delta to improve predictions of climate-warming methane and nitrous oxide.
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.
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.
ORNL Environmental Sciences Division Director Eric Pierce presented the division’s 2023 Distinguished Achievement Awards at the organization’s December all-hands meeting.
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%.