![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
- Advanced Manufacturing (11)
- Biology and Environment (8)
- Clean Energy (67)
- Climate and Environmental Systems (1)
- Computational Engineering (1)
- Computer Science (9)
- Fusion and Fission (1)
- Fusion Energy (3)
- Materials (24)
- Materials for Computing (5)
- National Security (10)
- Neutron Science (11)
- Nuclear Science and Technology (5)
- Quantum information Science (4)
- Supercomputing (60)
- Transportation Systems (1)
News Topics
- (-) 3-D Printing/Advanced Manufacturing (44)
- (-) Artificial Intelligence (20)
- (-) Computer Science (74)
- (-) Exascale Computing (5)
- (-) Grid (12)
- (-) Mercury (2)
- (-) Summit (26)
- (-) Transportation (27)
- Advanced Reactors (21)
- Big Data (18)
- Bioenergy (21)
- Biology (5)
- Biomedical (26)
- Biotechnology (3)
- Buildings (1)
- Chemical Sciences (5)
- Clean Water (7)
- Climate Change (10)
- Composites (3)
- Coronavirus (23)
- Critical Materials (3)
- Cybersecurity (9)
- Decarbonization (1)
- Energy Storage (29)
- Environment (48)
- Frontier (3)
- Fusion (19)
- High-Performance Computing (3)
- Isotopes (9)
- Machine Learning (13)
- Materials (2)
- Materials Science (59)
- Mathematics (2)
- Microscopy (13)
- Molten Salt (3)
- Nanotechnology (23)
- National Security (2)
- Neutron Science (48)
- Nuclear Energy (51)
- Physics (19)
- Polymers (9)
- Quantum Science (24)
- Security (5)
- Space Exploration (8)
- Sustainable Energy (32)
- Transformational Challenge Reactor (5)
Media Contacts
![As part of a preliminary study, ORNL scientists used critical location data collected from Twitter to map the location of certain power outages across the United States.](/sites/default/files/styles/list_page_thumbnail/public/2019-02/PowerOutageTweets_map_0.png?h=6448fdc1&itok=AUit-O2Y)
Gleaning valuable data from social platforms such as Twitter—particularly to map out critical location information during emergencies— has become more effective and efficient thanks to Oak Ridge National Laboratory.
![Laminations such as these are compiled to form the core of modern electric vehicle motors. ORNL has developed a software toolkit to speed the development of new motor designs and to improve the accuracy of their real-world performance.](/sites/default/files/styles/list_page_thumbnail/public/2019-02/Motors_OeRSTED_0.jpg?h=af53702d&itok=mT24R4WI)
Oak Ridge National Laboratory scientists have created open source software that scales up analysis of motor designs to run on the fastest computers available, including those accessible to outside users at the Oak Ridge Leadership Computing Facility.
OAK RIDGE, Tenn., Feb. 12, 2019—A team of researchers from the Department of Energy’s Oak Ridge and Los Alamos National Laboratories has partnered with EPB, a Chattanooga utility and telecommunications company, to demonstrate the effectiveness of metro-scale quantum key distribution (QKD).
![Researchers used machine learning methods on the ORNL Compute and Data Environment for Science, or CADES, to map vegetation communities in the Kougarok Watershed on the Seward Peninsula of Alaska. The colors denote different types of vegetation, such as w Researchers used machine learning methods on the ORNL Compute and Data Environment for Science, or CADES, to map vegetation communities in the Kougarok Watershed on the Seward Peninsula of Alaska. The colors denote different types of vegetation, such as w](/sites/default/files/styles/list_page_thumbnail/public/rs2019_highlight_plot_3d.png?itok=5bROV_ys)
A team of scientists led by Oak Ridge National Laboratory used machine learning methods to generate a high-resolution map of vegetation growing in the remote reaches of the Alaskan tundra.
![ORNL scientists used commuting behavior data from East Tennessee to demonstrate how machine learning models can easily accept new data, quickly re-train themselves and update predictions about commuting patterns. Credit: April Morton/Oak Ridge National La ORNL scientists used commuting behavior data from East Tennessee to demonstrate how machine learning models can easily accept new data, quickly re-train themselves and update predictions about commuting patterns. Credit: April Morton/Oak Ridge National La](/sites/default/files/styles/list_page_thumbnail/public/study_area_one_dest_2.jpg?itok=2cWFkQvW)
Oak Ridge National Laboratory geospatial scientists who study the movement of people are using advanced machine learning methods to better predict home-to-work commuting patterns.
![Supercomputing-Memory_boost1.jpg Supercomputing-Memory_boost1.jpg](/sites/default/files/styles/list_page_thumbnail/public/Supercomputing-Memory_boost1.jpg?itok=dDR8CnYC)
Scientists at Oak Ridge National Laboratory and Hypres, a digital superconductor company, have tested a novel cryogenic, or low-temperature, memory cell circuit design that may boost memory storage while using less energy in future exascale and quantum computing applications.
![Picture2.png Picture2.png](/sites/default/files/styles/list_page_thumbnail/public/Picture2_1.png?itok=IV4n9XEh)
Oak Ridge National Laboratory scientists studying fuel cells as a potential alternative to internal combustion engines used sophisticated electron microscopy to investigate the benefits of replacing high-cost platinum with a lower cost, carbon-nitrogen-manganese-based catalyst.
![Default image of ORNL entry sign](/sites/default/files/styles/list_page_thumbnail/public/2023-09/default-thumbnail.jpg?h=553c93cc&itok=N_Kd1DVR)
With a 3-D printed twist on an automotive icon, the Department of Energy’s Oak Ridge National Laboratory is showcasing additive manufacturing research at the 2015 North American International Auto Show in Detroit.