![Sphere that has the top right fourth removed (exposed) Colors from left are orange, dark blue with orange dots, light blue with horizontal lines, then black. Inside the exposure is green and black with boxes.](/sites/default/files/styles/featured_square_large/public/2024-06/slicer.jpg?h=56311bf6&itok=bCZz09pJ)
Filter News
Area of Research
News Topics
- (-) Chemical Sciences (9)
- (-) Composites (9)
- (-) Transportation (35)
- 3-D Printing/Advanced Manufacturing (31)
- Advanced Reactors (13)
- Artificial Intelligence (13)
- Big Data (16)
- Bioenergy (15)
- Biology (17)
- Biomedical (11)
- Biotechnology (3)
- Buildings (19)
- Clean Water (13)
- Climate Change (22)
- Computer Science (39)
- Coronavirus (11)
- Critical Materials (12)
- Cybersecurity (3)
- Decarbonization (8)
- Energy Storage (31)
- Environment (43)
- Exascale Computing (1)
- Frontier (1)
- Fusion (9)
- Grid (20)
- High-Performance Computing (11)
- Hydropower (6)
- Irradiation (2)
- Isotopes (5)
- ITER (3)
- Machine Learning (10)
- Materials (35)
- Materials Science (33)
- Mathematics (1)
- Mercury (3)
- Microscopy (11)
- Molten Salt (5)
- Nanotechnology (12)
- National Security (3)
- Net Zero (1)
- Neutron Science (27)
- Nuclear Energy (19)
- Partnerships (1)
- Physics (4)
- Polymers (9)
- Quantum Computing (4)
- Quantum Science (10)
- Security (1)
- Simulation (7)
- Space Exploration (10)
- Statistics (1)
- Summit (6)
- Sustainable Energy (44)
Media Contacts
![Layering on the strength](/sites/default/files/styles/list_page_thumbnail/public/2019-09/Z-pinning-printed%20wall_ORNL-2_0.png?h=c8a62123&itok=EnqQdQih)
A team including Oak Ridge National Laboratory and University of Tennessee researchers demonstrated a novel 3D printing approach called Z-pinning that can increase the material’s strength and toughness by more than three and a half times compared to conventional additive manufacturing processes.
![Batteries—Polymers that bind](/sites/default/files/styles/list_page_thumbnail/public/2019-06/Batteries-Polymers_that_bind_0.png?h=dec22bcf&itok=oJ7mroY1)
A team of researchers at Oak Ridge National Laboratory have demonstrated that designed synthetic polymers can serve as a high-performance binding material for next-generation lithium-ion batteries.
![Transportation Energy Data Book Edition 37](/sites/default/files/styles/list_page_thumbnail/public/2019-03/Transportation-Logging_the_miles_ORNL_0.jpg?h=ade3edc7&itok=wGiEijHl)
Oak Ridge National Laboratory’s latest Transportation Energy Data Book: Edition 37 reports that the number of vehicles nationwide is growing faster than the population, with sales more than 17 million since 2015, and the average household vehicle travels more than 11,000 miles per year.
![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.
![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.
![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.
![X1800-REED-Maritime Risk Symposium 2018 logo-AM V5-01.jpg X1800-REED-Maritime Risk Symposium 2018 logo-AM V5-01.jpg](/sites/default/files/styles/list_page_thumbnail/public/X1800-REED-Maritime%20Risk%20Symposium%202018%20logo-AM%20V5-01.jpg?itok=_AN4HV63)
Thought leaders from across the maritime community came together at Oak Ridge National Laboratory to explore the emerging new energy landscape for the maritime transportation system during the Ninth Annual Maritime Risk Symposium.
![Autonomous_vehicle_simulation_ORNL.jpg Autonomous_vehicle_simulation_ORNL.jpg](/sites/default/files/styles/list_page_thumbnail/public/Autonomous_vehicle_simulation_ORNL.jpg?itok=2pnITULi)
Self-driving cars promise to keep traffic moving smoothly and reduce fuel usage, but proving those advantages has been a challenge with so few connected and automated vehicles, or CAVs, currently on the road.
![California charging EV station map California charging EV station map](/sites/default/files/styles/list_page_thumbnail/public/news/images/Untitled-1%20%281%29.jpg?itok=NkA3kv-0)
Officials responsible for anticipating the demand for electric vehicle charging stations could get help through a sophisticated new method developed at Oak Ridge National Laboratory. The method considers electric vehicle volume and the random timing of vehicles arriving at cha...
![ORNL’s Frank Combs and Michael Starr of the U.S. Armed Forces (driver) work in ORNL’s Vehicle Security Laboratory to evaluate a prototype device that can detect network intrusions in all modern vehicles. Credit: Carlos Jones/ORNL, U.S. Dept. of Energy ORNL’s Frank Combs and Michael Starr of the U.S. Armed Forces (driver) work in ORNL’s Vehicle Security Laboratory to evaluate a prototype device that can detect network intrusions in all modern vehicles. Credit: Carlos Jones/ORNL, U.S. Dept. of Energy](/sites/default/files/styles/list_page_thumbnail/public/news/images/01_Cybersecurity_guarding_autonomous_vehicles.jpg?itok=qaErb8Ia)
A new Oak Ridge National Laboratory-developed method promises to protect connected and autonomous vehicles from possible network intrusion. Researchers built a prototype plug-in device designed to alert drivers of vehicle cyberattacks. The prototype is coded to learn regular timing...