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Media Contacts
![Joon-Seok Kim Credit: Genevieve Martin/ORNL, U.S. Dept. of Energy](/sites/default/files/styles/list_page_thumbnail/public/2024-05/joon-seok.jpg?h=d9b3a08b&itok=qiPgBrWQ)
Researchers at ORNL are using a machine-learning model to answer ‘what if’ questions stemming from major events that impact large numbers of people. By simulating an event, such as extreme weather, researchers can see how people might respond to adverse situations, and those outcomes can be used to improve emergency planning.
![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](/sites/default/files/styles/list_page_thumbnail/public/2024-05/2024-P07278R.jpg?h=c6980913&itok=lVwfnfEq)
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.
![Quietly making noise: Measuring differential privacy could balance meaningful analytics and identity protection](/sites/default/files/styles/list_page_thumbnail/public/2024-04/AdobeStock_599537692.jpeg?h=8059516b&itok=oDcA1WvL)
To balance personal safety and research innovation, researchers at ORNL are employing a mathematical technique known as differential privacy to provide data privacy guarantees.
Simulations performed on the Summit supercomputer at ORNL are cutting through that time and expense by helping researchers digitally customize the ideal alloy.
![New research predicts peak groundwater extraction for key basins around the globe by the year 2050. The map indicates groundwater storage trends for Earth’s 37 largest aquifers using data from the NASA Jet Propulsion Laboratory GRACE satellite. Credit: NASA.](/sites/default/files/styles/list_page_thumbnail/public/2024-04/GroundwaterGRACE%20%281%29.jpg?h=3c857b1a&itok=g_tWUVHW)
Groundwater withdrawals are expected to peak in about one-third of the world’s basins by 2050, potentially triggering significant trade and agriculture shifts, a new analysis finds.
![Campus](/sites/default/files/styles/list_page_thumbnail/public/2024-04/sunset_visitor-center.png?h=10d202d3&itok=tGr8drzM)
Rishi Pillai and his research team from ORNL will receive a Best Paper award from the American Society of Mechanical Engineers International Gas Turbine Institute in June at the Turbo Expo 2024 in London.
![Three ORNL researchers receive Outstanding Young Manufacturing Engineer Award](/sites/default/files/styles/list_page_thumbnail/public/2024-04/2013-P05160-cropped_1.jpg?h=55be468c&itok=V0dSpq0r)
The Society of Manufacturing Engineers has honored three Oak Ridge National Laboratory researchers with the 2024 SME Susan Smyth Outstanding Young Manufacturing Engineer Award.
![ORNL’s Erin Webb is co-leading a new Circular Bioeconomy Systems Convergent Research Initiative focused on advancing production and use of renewable carbon from Tennessee to meet societal needs. Credit: Genevieve Martin/ORNL, U.S. Dept. of Energy](/sites/default/files/styles/list_page_thumbnail/public/2024-04/Erin%20Webb%202022-P09128.jpg?h=c6980913&itok=pCWWVGaU)
ORNL’s Erin Webb is co-leading a new Circular Bioeconomy Systems Convergent Research Initiative focused on advancing production and use of renewable carbon from Tennessee to meet societal needs.
![ORNL’s Suhas Sreehari explains the algebraic and topological foundations of representation systems, used in generative AI technology such as large language models. Credit: Lena Shoemaker/ORNL, U.S. Dept. of Energy](/sites/default/files/styles/list_page_thumbnail/public/2024-04/powered%20by%20match.jpg?h=384e2afb&itok=wJegcDZm)
In the age of easy access to generative AI software, user can take steps to stay safe. Suhas Sreehari, an applied mathematician, identifies misconceptions of generative AI that could lead to unintentionally bad outcomes for a user.
![Credit: Tyler Spano/ORNL, U.S. Dept. of Energy](/sites/default/files/styles/list_page_thumbnail/public/2024-04/liz.jpg?h=ab2675cd&itok=jVO3_Ggr)
Nuclear nonproliferation scientists at ORNL have published the Compendium of Uranium Raman and Infrared Experimental Spectra, a public database and analysis of structure-spectral relationships for uranium minerals. This first-of-its-kind dataset and corresponding analysis fill a key gap in the existing body of knowledge for mineralogists and actinide scientists.