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Jiafu Mao, left, and Yaoping Wang discuss their analysis of urban and rural vegetation resilience across the United States in the EVEREST visualization lab at ORNL. Credit: Carlos Jones, ORNL/U.S. Dept. of Energy

Scientists at ORNL completed a study of how well vegetation survived extreme heat events in both urban and rural communities across the country in recent years. The analysis informs pathways for climate mitigation, including ways to reduce the effect of urban heat islands.

Testing with ORNL tribology equipment found that new ionic liquid-based lubricant additives developed for water turbines significantly reduced friction and equipment wear. Credit: Genevieve Martin, ORNL/U.S. Dept. of Energy

Scientists at the Department of Energy’s Oak Ridge National Laboratory have developed lubricant additives that protect both water turbine equipment and the surrounding environment.

ORNL engineer Canan Karakaya uses computational modeling to design and improve chemical reactors and how they are operated to convert methane, carbon dioxide, ammonia or ethanol into higher-value chemicals or energy-dense fuels. Credit: Carlos Jones/ORNL, U.S. Dept. of Energy

Canan Karakaya, a R&D Staff member in the Chemical Process Scale-Up group at ORNL, was inspired to become a chemical engineer after she experienced a magical transformation that turned ammonia gas into ammonium nitrate, turning a liquid into white flakes gently floating through the air. 

ORNL’s Kate Evans has been awarded the 2024 Society for Industrial and Applied Mathematicians Activity Group on Mathematics of Planet Earth Prize.

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. 

ORNL

Two different teams that included Oak Ridge National Laboratory employees were honored Feb. 20 with Secretary’s Honor Achievement Awards from the Department of Energy. This is DOE's highest form of employee recognition. 

: ORNL climate modeling expertise contributed to an AI-backed model that assesses global emissions of ammonia from croplands now and in a warmer future, while identifying mitigation strategies. This map highlights croplands around the world. Credit: U.S. Geological Survey

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.

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

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 Associate Laboratory Director for Computing and Computational Sciences. Credit: Carlos Jones/ORNL, U.S. Dept. of Energy

Gina Tourassi, associate laboratory director for computing and computational sciences at the US Department of Energy’s (DOE’s) Oak Ridge National Laboratory, has been named a fellow of the Institute of Electrical and Electronics Engineers, the world’s largest organization for technical professionals.

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.

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.

The illustration depicts ocean surface currents simulated by MPAS-Ocean. Credit: Los Alamos National Laboratory, E3SM, U.S. Dept. of Energy

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%.