![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
- Advanced Manufacturing (2)
- Biology and Environment (6)
- Clean Energy (22)
- Computational Engineering (2)
- Computer Science (1)
- Fusion and Fission (7)
- Fusion Energy (6)
- Isotopes (1)
- Materials (11)
- Materials for Computing (3)
- Mathematics (1)
- National Security (3)
- Neutron Science (4)
- Nuclear Science and Technology (2)
- Quantum information Science (2)
- Supercomputing (8)
- Transportation Systems (2)
News Type
News Topics
- (-) Advanced Reactors (7)
- (-) Biomedical (7)
- (-) Chemical Sciences (5)
- (-) Climate Change (9)
- (-) Cybersecurity (9)
- (-) Fusion (12)
- (-) Molten Salt (1)
- (-) Transportation (21)
- 3-D Printing/Advanced Manufacturing (29)
- Artificial Intelligence (11)
- Big Data (8)
- Bioenergy (9)
- Biology (9)
- Biotechnology (2)
- Buildings (8)
- Clean Water (8)
- Composites (8)
- Computer Science (39)
- Coronavirus (7)
- Critical Materials (4)
- Decarbonization (2)
- Energy Storage (19)
- Environment (26)
- Exascale Computing (1)
- Frontier (5)
- Grid (12)
- High-Performance Computing (10)
- Isotopes (7)
- ITER (3)
- Machine Learning (5)
- Materials (27)
- Materials Science (31)
- Mathematics (1)
- Microscopy (10)
- Nanotechnology (11)
- National Security (3)
- Net Zero (1)
- Neutron Science (24)
- Nuclear Energy (12)
- Physics (5)
- Polymers (5)
- Quantum Computing (4)
- Quantum Science (16)
- Security (3)
- Space Exploration (6)
- Statistics (1)
- Summit (10)
- Sustainable Energy (33)
Media Contacts
![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.
![Default image of ORNL entry sign](/sites/default/files/styles/list_page_thumbnail/public/2023-09/default-thumbnail.jpg?h=553c93cc&itok=N_Kd1DVR)
Scientists of the Next-Generation Ecosystem Experiments are blogging from the Arctic this summer. Follow their adventures at http://ngee-arctic.blogspot.com/. Participants share troubles and triumphs from the field in entries with headings like "Flying Wild Alaska" and "Hitting the Tundra." "The b...