![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
- (-) Artificial Intelligence (13)
- (-) Biology (1)
- (-) Composites (3)
- (-) Nanotechnology (6)
- (-) Polymers (2)
- (-) Security (2)
- (-) Space Exploration (4)
- (-) Transportation (14)
- 3-D Printing/Advanced Manufacturing (16)
- Advanced Reactors (7)
- Big Data (9)
- Bioenergy (11)
- Biomedical (5)
- Biotechnology (1)
- Clean Water (5)
- Computer Science (41)
- Cybersecurity (7)
- Energy Storage (9)
- Environment (23)
- Exascale Computing (3)
- Frontier (2)
- Fusion (6)
- Grid (5)
- Isotopes (1)
- Machine Learning (5)
- Materials Science (22)
- Mercury (2)
- Microscopy (5)
- Molten Salt (1)
- Neutron Science (20)
- Nuclear Energy (17)
- Physics (8)
- Quantum Science (10)
- Summit (9)
- Sustainable Energy (8)
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.
![ORNL alanine_graphic.jpg ORNL alanine_graphic.jpg](/sites/default/files/styles/list_page_thumbnail/public/ORNL%20alanine_graphic.jpg?itok=iRLfcOw-)
OAK RIDGE, Tenn., Jan. 31, 2019—A new electron microscopy technique that detects the subtle changes in the weight of proteins at the nanoscale—while keeping the sample intact—could open a new pathway for deeper, more comprehensive studies of the basic building blocks of life.
![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.
![As hurricanes formed in the Gulf Coast, ORNL activated a computing technique to quickly gather building structure data from Texas’ coastal counties. Credit: Mark Tuttle/Oak Ridge National Laboratory, U.S. Dept. of Energy As hurricanes formed in the Gulf Coast, ORNL activated a computing technique to quickly gather building structure data from Texas’ coastal counties. Credit: Mark Tuttle/Oak Ridge National Laboratory, U.S. Dept. of Energy](/sites/default/files/styles/list_page_thumbnail/public/01%201%20-%20Impacts%20r1.jpg?itok=D1FzgK0y)
Geospatial scientists at Oak Ridge National Laboratory have developed a novel method to quickly gather building structure datasets that support emergency response teams assessing properties damaged by Hurricanes Harvey and Irma. By coupling deep learning with high-performance comp...
![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...
![ORNL Image](/sites/default/files/styles/list_page_thumbnail/public/2017-P04962.jpg?h=dafbaa5b&itok=kG3bP2Q9)
Working backwards has moved Josh Michener’s research far forward as he uses evolution and genetics to engineer microbes for better conversion of plants into biofuels and biochemicals. In his work for the BioEnergy Science Center at ORNL, for instance, “we’ve gotten good at engineering microbes th...
![ORNL Image](/sites/default/files/styles/list_page_thumbnail/public/2017-S00094_2.jpg?itok=ZGWBnMOv)
Researchers used neutrons to probe a running engine at ORNL’s Spallation Neutron Source
![Manufacturing_tailoring_performance Manufacturing_tailoring_performance](/sites/default/files/styles/list_page_thumbnail/public/news/images/Manufacturing_tailoring_performance.jpg?itok=ijYcyHyE)
A new manufacturing method created by Oak Ridge National Laboratory and Rice University combines 3D printing with traditional casting to produce damage-tolerant components composed of multiple materials. Composite components made by pouring an aluminum alloy over a printed steel lattice showed an order of magnitude greater damage tolerance than aluminum alone.