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Media Contacts
![State and Local Economic Development Award](/sites/default/files/styles/list_page_thumbnail/public/2023-01/FLCAward3_thumbnail.png?h=d1cb525d&itok=FKj_T8JY)
A partnership of ORNL, the Tennessee Department of Economic and Community Development, the Community Reuse Organization of East Tennessee and TVA that aims to attract nuclear energy-related firms to Oak Ridge has been recognized with a state and local economic development award from the Federal Laboratory Consortium.
![A group of people standing outside in front of trees and buildings](/sites/default/files/styles/list_page_thumbnail/public/2022-11/2022-P10952.jpg?h=8f9cfe54&itok=Wd2coEC5)
Nine student physicists and engineers from the #1-ranked Nuclear Engineering and Radiological Sciences Program at the University of Michigan, or UM, attended a scintillation detector workshop at Oak Ridge National Laboratory Oct. 10-13.
![Dongarra in 2019 with Oak Ridge National Laboratory's Summit supercomputer](/sites/default/files/styles/list_page_thumbnail/public/2022-03/I%29%20Dongarra_IBM_Summit_Superomputer.jpeg?h=4bf1c8f5&itok=9sM8m0Iz)
A force within the supercomputing community, Jack Dongarra developed software packages that became standard in the industry, allowing high-performance computers to become increasingly more powerful in recent decades.
![Three ORNL scientists have been elected fellows of the American Association for the Advancement of Science, or AAAS, the world’s largest general scientific society and publisher of the Science family of journals. Credit: ORNL, U.S. Dept. of Energy](/sites/default/files/styles/list_page_thumbnail/public/2022-01/AAAS_fellows_resize_0.jpg?h=e91a75a9&itok=y20mbH61)
Three ORNL scientists have been elected fellows of the American Association for the Advancement of Science, or AAAS, the world’s largest general scientific society and publisher of the Science family of journals.
![An open-source code developed by an ORNL-led team could provide new insights into the everyday operation of the nation’s power grid. Credit: Pixabay](/sites/default/files/styles/list_page_thumbnail/public/2021-10/digitization-gef50ab16f_1920_0.jpg?h=e5aec6c8&itok=55oFYLLz)
Oak Ridge National Laboratory, University of Tennessee and University of Central Florida researchers released a new high-performance computing code designed to more efficiently examine power systems and identify electrical grid disruptions, such as
![Six ORNL scientists have been elected as fellows to the American Association for the Advancement of Science, or AAAS. Credit: ORNL, U.S. Dept. of Energy](/sites/default/files/styles/list_page_thumbnail/public/2020-11/AAASfellows.jpg?h=d761c044&itok=opKRkA17)
Six ORNL scientists have been elected as fellows to the American Association for the Advancement of Science, or AAAS.
![GIS – LandScan goes public](/sites/default/files/styles/list_page_thumbnail/public/2020-05/sanfran%20%281%29_2.png?h=ea18fbc4&itok=c_VbFqAC)
Oak Ridge National Laboratory’s high-resolution population distribution database, LandScan USA, became permanently available to researchers in time to aid the response to the novel coronavirus pandemic.
![A new computational approach by ORNL can more quickly scan large-scale satellite images, such as these of Puerto Rico, for more accurate mapping of complex infrastructure like buildings. Credit: Maxar Technologies and Dalton Lunga/Oak Ridge National Laboratory, U.S. Dept. of Energy](/sites/default/files/styles/list_page_thumbnail/public/2020-02/Puerto_Rico_Resflow9.png?h=a0a1befd&itok=5n2fss_e)
A novel approach developed by scientists at ORNL can scan massive datasets of large-scale satellite images to more accurately map infrastructure – such as buildings and roads – in hours versus days.
![Smart Neighborhood homes](/sites/default/files/styles/list_page_thumbnail/public/2020-01/04.09.TD-SMartHome_0.jpg?h=5b5a5437&itok=22S5Tle1)
To better determine the potential energy cost savings among connected homes, researchers at Oak Ridge National Laboratory developed a computer simulation to more accurately compare energy use on similar weather days.
![Project bridges compute staff, resources at ORNL and VA health data to speed suicide risk screening for US veterans. Image Credit: Carlos Jones, ORNL](/sites/default/files/styles/list_page_thumbnail/public/2019-08/VA_REACHVET1%5B6%5D_0.jpg?h=173ee000&itok=-eA5t15j)
In collaboration with the Department of Veterans Affairs, a team at Oak Ridge National Laboratory has expanded a VA-developed predictive computing model to identify veterans at risk of suicide and sped it up to run 300 times faster, a gain that could profoundly affect the VA’s ability to reach susceptible veterans quickly.