![Weyl semimetal](/sites/default/files/styles/featured_square_large/public/2024-08/Picture4.jpg?h=b38bf506&itok=nYXXiLDs)
Filter News
Area of Research
- Advanced Manufacturing (11)
- Biology and Environment (7)
- Building Technologies (1)
- Clean Energy (60)
- Computational Biology (1)
- Computer Science (2)
- Electricity and Smart Grid (1)
- Fusion Energy (2)
- Isotopes (3)
- Materials (17)
- Materials for Computing (3)
- National Security (5)
- Neutron Science (5)
- Nuclear Science and Technology (3)
- Quantum information Science (1)
- Sensors and Controls (1)
- Supercomputing (10)
- Transportation Systems (2)
News Type
News Topics
- (-) 3-D Printing/Advanced Manufacturing (31)
- (-) Biomedical (11)
- (-) Cybersecurity (3)
- (-) Grid (21)
- (-) Isotopes (5)
- (-) Mercury (3)
- (-) Physics (4)
- (-) Space Exploration (10)
- (-) Summit (6)
- (-) Transportation (35)
- Advanced Reactors (13)
- Artificial Intelligence (13)
- Big Data (17)
- Bioenergy (16)
- Biology (18)
- Biotechnology (3)
- Buildings (19)
- Chemical Sciences (11)
- Clean Water (13)
- Climate Change (23)
- Composites (9)
- Computer Science (40)
- Coronavirus (11)
- Critical Materials (12)
- Decarbonization (9)
- Energy Storage (31)
- Environment (44)
- Exascale Computing (1)
- Fossil Energy (1)
- Frontier (1)
- Fusion (9)
- High-Performance Computing (11)
- Hydropower (6)
- Irradiation (2)
- ITER (3)
- Machine Learning (11)
- Materials (35)
- Materials Science (34)
- Mathematics (2)
- Microscopy (11)
- Molten Salt (5)
- Nanotechnology (12)
- National Security (3)
- Net Zero (2)
- Neutron Science (27)
- Nuclear Energy (19)
- Partnerships (1)
- Polymers (9)
- Quantum Computing (4)
- Quantum Science (10)
- Security (1)
- Simulation (7)
- Statistics (1)
- Sustainable Energy (45)
Media Contacts
![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.
![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.
![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.
![Nuclear—Deep space travel Nuclear—Deep space travel](/sites/default/files/styles/list_page_thumbnail/public/Screen%20Shot%202018-12-19%20at%2010.29.32%20AM.png?itok=hq0dlVIf)
By automating the production of neptunium oxide-aluminum pellets, Oak Ridge National Laboratory scientists have eliminated a key bottleneck when producing plutonium-238 used by NASA to fuel deep space exploration.
![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.
![2018-P07635 BL-6 user - Univ of Guelph-6004R_sm[2].jpg 2018-P07635 BL-6 user - Univ of Guelph-6004R_sm[2].jpg](/sites/default/files/styles/list_page_thumbnail/public/2018-P07635%20BL-6%20user%20-%20Univ%20of%20Guelph-6004R_sm%5B2%5D.jpg?itok=DUdZNt_q)
A team of scientists, led by University of Guelph professor John Dutcher, are using neutrons at ORNL’s Spallation Neutron Source to unlock the secrets of natural nanoparticles that could be used to improve medicines.
![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.
![Physics_silicon-detectors.jpg](/sites/default/files/styles/list_page_thumbnail/public/Physics_silicon-detectors.jpg?h=c920d705&itok=Q1fP5ZTi)
Physicists turned to the “doubly magic” tin isotope Sn-132, colliding it with a target at Oak Ridge National Laboratory to assess its properties as it lost a neutron to become Sn-131.