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Media Contacts
![Using a better modeling framework, with data collected from Mississippi Delta marshes, scientists are able to improve the predictions of methane and other greenhouse gas emissions. Credit: Matthew Berens/ORNL, U.S Dept. of Energy](/sites/default/files/styles/list_page_thumbnail/public/2024-01/picture1_0.jpg?itok=uQVJerN0)
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.
![ORNL’s Tomás Rush examines a culture as part of his research into the plant-fungus relationship that can help or hinder ecosystem health. Credit: Genevieve Martin/ORNL, U.S. Dept. of Energy](/sites/default/files/styles/list_page_thumbnail/public/2024-01/2022-p09834_0.jpg?h=c6980913&itok=iHPtg7RM)
New computational framework speeds discovery of fungal metabolites, key to plant health and used in drug therapies and for other uses.
![Researchers at Corning have found that understanding the stability of the rings of atoms in glass materials can help predict the performance of glass products.](/sites/default/files/styles/list_page_thumbnail/public/2024-01/picture2.png?h=342db57d&itok=yUdVp1Za)
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.
![Prasanna Balaprakash, who leads ORNL’s AI Initiative, participated in events hosted by the White House Office of Science and Technology Policy and the Task Force on American Innovation to discuss the challenges and opportunities posed by AI. Credit: Brian Mosley/Computing Research Association](/sites/default/files/styles/list_page_thumbnail/public/2024-01/01_tfai_decon_ai_20_-_10-26-23_0.jpg?h=411c976c&itok=kRKOW1KH)
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.
![2023 Top Science Achievements at SNS & HFIR](/sites/default/files/styles/list_page_thumbnail/public/2023-12/23-G08001-SNS-Top-Story-Image-pcg.jpg?h=1f0bc3a8&itok=3_ZyuAAO)
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.
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%.
![Alex May, pictured above, is the first and only full-time data curator at the Department of Energy’s Oak Ridge Leadership Computing Facility. Credit: Carlos Jones and Wikimedia Commons, background/ORNL, U.S. Dept. of Energy](/sites/default/files/styles/list_page_thumbnail/public/2023-12/2023-P18433%20%281%29_0.jpg?h=8f9cfe54&itok=DQKdmnrN)
![In a proposed carbon-capture method, magnesium oxide crystals on the ground bind to carbon dioxide molecules from the surrounding air, triggering the formation of magnesium carbonate. The magnesium carbonate is then heated to convert it back to magnesium oxide and release the carbon dioxide for placement underground, or sequestration. Credit: Adam Malin/ORNL, U.S. Dept. of Energy](/sites/default/files/styles/list_page_thumbnail/public/2023-12/Graphic-DAC-magnesium-oxide_0.jpg?h=1254d433&itok=otlbgWaQ)
Magnesium oxide is a promising material for capturing carbon dioxide directly from the atmosphere and injecting it deep underground to limit the effects of climate change. ORNL scientists are exploring ways to overcome an obstacle to making the technology economical.
![Frontier’s exascale power enables the Simple Cloud-Resolving E3SM Atmosphere Model to run years’ worth of climate simulations at unprecedented speed and scale. Credit: Ben Hillman/Sandia National Laboratories, U.S. Dept. of Energy](/sites/default/files/styles/list_page_thumbnail/public/2023-12/E3SM-MMF.png?h=21f5ce54&itok=dsj1Hwvc)
A 19-member team of scientists from across the national laboratory complex won the Association for Computing Machinery’s 2023 Gordon Bell Special Prize for Climate Modeling for developing a model that uses the world’s first exascale supercomputer to simulate decades’ worth of cloud formations.
![A Univ. of Michigan-led team used Frontier, the world’s first exascale supercomputer, to simulate a system of nearly 75,000 magnesium atoms at near-quantum accuracy. Credit: SC23](/sites/default/files/styles/list_page_thumbnail/public/2023-12/Gavini-SC23_1116_awards-20.jpg?h=c6980913&itok=LQLYh4jz)
A team of eight scientists won the Association for Computing Machinery’s 2023 Gordon Bell Prize for their study that used the world’s first exascale supercomputer to run one of the largest simulations of an alloy ever and achieve near-quantum accuracy.