![White car (Porsche Taycan) with the hood popped is inside the building with an american flag on the wall.](/sites/default/files/styles/featured_square_large/public/2024-06/2024-P09317.jpg?h=8f9cfe54&itok=m6sQhZRq)
Filter News
Area of Research
- (-) National Security (5)
- Biological Systems (1)
- Biology and Environment (25)
- Clean Energy (11)
- Computational Biology (2)
- Computational Engineering (1)
- Computer Science (1)
- Fusion and Fission (2)
- Fusion Energy (1)
- Isotopes (5)
- Materials (10)
- Materials for Computing (3)
- Neutron Science (15)
- Nuclear Science and Technology (2)
- Supercomputing (71)
News Type
News Topics
- (-) Biomedical (2)
- (-) Exascale Computing (1)
- (-) Summit (2)
- 3-D Printing/Advanced Manufacturing (2)
- Advanced Reactors (1)
- Artificial Intelligence (12)
- Big Data (6)
- Bioenergy (3)
- Biology (5)
- Biotechnology (1)
- Buildings (1)
- Chemical Sciences (2)
- Climate Change (5)
- Computer Science (19)
- Coronavirus (2)
- Cybersecurity (19)
- Decarbonization (2)
- Energy Storage (2)
- Environment (5)
- Frontier (1)
- Fusion (1)
- Grid (6)
- High-Performance Computing (4)
- Machine Learning (12)
- Materials (2)
- Materials Science (3)
- Nanotechnology (1)
- National Security (34)
- Neutron Science (4)
- Nuclear Energy (5)
- Partnerships (4)
- Physics (1)
- Quantum Science (1)
- Security (11)
- Simulation (1)
- Sustainable Energy (3)
- Transportation (2)
Media Contacts
![Michelle Kidder received the lab’s Director’s Award for Outstanding Individual Accomplishment in Science and Technology for her decades-long work mentoring students, teachers and early-career staff. Credit: Carlos Jones/ORNL, U.S. Dept. of Energy](/sites/default/files/styles/list_page_thumbnail/public/2022-11/2018-P04785_0.png?h=7a8a8cdf&itok=hysTNqXX)
Laboratory Director Thomas Zacharia presented five Director’s Awards during Saturday night's annual Awards Night event hosted by UT-Battelle, which manages ORNL for the Department of Energy.
![MDF Exterior](/sites/default/files/styles/list_page_thumbnail/public/2022-06/2021-p07609.jpg?h=be3e4b3a&itok=YfKK7Wy2)
ORNL scientists will present new technologies available for licensing during the annual Technology Innovation Showcase. The event is 9 a.m. to 3 p.m. Thursday, June 16, at the Manufacturing Demonstration Facility at ORNL’s Hardin Valley campus.
![The ORNL researchers’ findings may enable better detection of uranium tetrafluoride hydrate, a little-studied byproduct of the nuclear fuel cycle, and better understanding of how environmental conditions influence the chemical behavior of fuel cycle materials. Credit: Kevin Pastoor/Colorado School of Mines](/sites/default/files/styles/list_page_thumbnail/public/2022-05/UF4%20hydrate.png?h=d318f057&itok=spT-Dg48)
ORNL researchers used the nation’s fastest supercomputer to map the molecular vibrations of an important but little-studied uranium compound produced during the nuclear fuel cycle for results that could lead to a cleaner, safer world.
![ORNL, VA and Harvard researchers developed a sparse matrix full of anonymized information on what is thought to be the largest cohort of healthcare data used for this type of research in the U.S. The matrix can be probed with different methods, such as KESER, to gain new insights into human health. Credit: Nathan Armistead/ORNL, U.S. Dept. of Energy](/sites/default/files/styles/list_page_thumbnail/public/2022-04/2022-G00330_KESER%20Illustration_0.jpg?h=1cb48fc4&itok=c6ZuDdDg)
A team of researchers has developed a novel, machine learning–based technique to explore and identify relationships among medical concepts using electronic health record data across multiple healthcare providers.
![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.