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Media Contacts
![caption](/sites/default/files/styles/list_page_thumbnail/public/2024-07/24-G03173_Cochran_NSSD%20JSU%20TTU%20MOUs%20Article%20Image_R5G.png?h=44b879e5&itok=xd0oS_yb)
The National Security Sciences Directorate within the Department of Energy’s Oak Ridge National Laboratory has signed a memoranda of understanding with Jackson State University and with Tennessee Tech University. The MOUs detail ORNL’s intention to work with each university to enhance research and educational opportunities in nuclear science and engineering.
ORNL drone and geospatial team becomes first to map the Coca River in the Amazon basin as erosion and sediment threaten Ecuador’s lands.
![3D printed “Frankenstein design” collimator show the “scars” where the individual parts are joined](/sites/default/files/styles/list_page_thumbnail/public/2024-04/2024-P03207%20collimator%20with%20scars%20highlighted.jpg?h=036a71b7&itok=4aO2i21j)
Scientists at ORNL have developed 3-D-printed collimator techniques that can be used to custom design collimators that better filter out noise during different types of neutron scattering experiments
![ORNL intern Jack Orebaugh holds the drone used in his research to help locate human remains. Credit: Lena Shoemaker/ORNL, U.S. Dept. of Energy](/sites/default/files/styles/list_page_thumbnail/public/2024-01/jack.jpg?h=0261ddcd&itok=yZ9N5dAh)
Jack Orebaugh, a forensic anthropology major at the University of Tennessee, Knoxville, has a big heart for families with missing loved ones. When someone disappears in an area of dense vegetation, search and recovery efforts can be difficult, especially when a missing person’s last location is unknown. Recognizing the agony of not knowing what happened to a family or friend, Orebaugh decided to use his internship at the Department of Energy’s Oak Ridge National Laboratory to find better ways to search for lost and deceased people using cameras and drones.
![The AI agent, incorporating a language model-based molecular generator and a graph neural network-based molecular property predictor, processes a set of user-provided molecules (green) and produces/suggests new molecules (red) with desired chemical/physical properties (i.e. excitation energy). Image credit: Pilsun You, Jason Smith/ORNL, U.S. DOE](/sites/default/files/styles/list_page_thumbnail/public/2023-12/image001_0.png?h=16ec4b77&itok=KtCjteSq)
A team of computational scientists at ORNL has generated and released datasets of unprecedented scale that provide the ultraviolet visible spectral properties of over 10 million organic molecules.
![Image of circuitry representing AI.](/sites/default/files/styles/list_page_thumbnail/public/2023-11/ai-generic_0.jpg?h=7a6e80fd&itok=kM92w4I_)
Research performed by a team, including scientists from ORNL and Argonne National Laboratory, has resulted in a Best Paper Award at the 19th IEEE International Conference on eScience.
![NEXTGENCOMPUTING students learned fundamental computing concepts through an HPC Crash Course before applying those concepts to an AI-based team project. From left to right, front row: Saahithi Gorti, Hannah Bao, Pragya Nidhi. Middle row: Kaiya Barnes, Brianna Andrews, Aninditha Nair, Olivia Heng, Disha Maheshwari, Emma Bohse, Sachi Griffin, Kevin Peng. Back row, Kieran Marci, Ronak Patel, Michael Batchelor, Matthew Tan, Richard Sances, Dhanvi Bharadwaj, Prabhash G C. Credit: ORNL](/sites/default/files/styles/list_page_thumbnail/public/2023-12/Summit%20Group%20Photo.jpg?h=71976bb4&itok=MJR6GHh2)
This summer, ORNL welcomed more than 500 students to campus through the lab’s range of internship programs, which are offered in areas such as biology, national security and computing.
![A new method for analyzing climate models brings together information from various lines of evidence to represent Earth’s climate sensitivity. Credit: Jason Smith/ORNL, U.S. Dept. of Energy](/sites/default/files/styles/list_page_thumbnail/public/2023-11/climate-models.png?h=b655f2ac&itok=l5A4_3yJ)
Researchers from institutions including ORNL have created a new method for statistically analyzing climate models that projects future conditions with more fidelity.
![ORNL researchers are establishing a digital thread of data, algorithms and workflows to produce a continuously updated model of earth systems.](/sites/default/files/styles/list_page_thumbnail/public/2023-11/MicrosoftTeams-image%20%2823%29_0.png?h=c6980913&itok=cK99Pg3y)
Digital twins are exactly what they sound like: virtual models of physical reality that continuously update to reflect changes in the real world.
![Hilda Klasky](/sites/default/files/styles/list_page_thumbnail/public/2023-12/HildaKlaskyMug_0.jpeg?h=5b728bb6&itok=aVEFR1-o)
Hilda Klasky, a research scientist in ORNL’s Computing and Computational Sciences Directorate, has been named a fellow of the American Medical Informatics Association.