Filter News
Area of Research
- (-) Climate and Environmental Systems (4)
- (-) Supercomputing (42)
- Advanced Manufacturing (14)
- Biological Systems (2)
- Biology and Environment (100)
- Biology and Soft Matter (1)
- Building Technologies (1)
- Clean Energy (92)
- Computational Engineering (2)
- Computer Science (5)
- Fusion and Fission (6)
- Fusion Energy (2)
- Materials (24)
- Materials for Computing (3)
- Mathematics (1)
- National Security (14)
- Neutron Science (11)
- Nuclear Science and Technology (6)
- Quantum information Science (1)
News Type
News Topics
- (-) 3-D Printing/Advanced Manufacturing (2)
- (-) Bioenergy (3)
- (-) Environment (21)
- (-) Exascale Computing (13)
- (-) Frontier (14)
- (-) Machine Learning (8)
- (-) Mathematics (1)
- Advanced Reactors (1)
- Artificial Intelligence (22)
- Big Data (17)
- Biology (8)
- Biomedical (11)
- Biotechnology (1)
- Buildings (2)
- Chemical Sciences (2)
- Climate Change (16)
- Computer Science (62)
- Coronavirus (9)
- Critical Materials (3)
- Cybersecurity (2)
- Decarbonization (3)
- Energy Storage (2)
- Fusion (1)
- Grid (1)
- High-Performance Computing (23)
- Materials (5)
- Materials Science (9)
- Microscopy (2)
- Nanotechnology (6)
- National Security (3)
- Net Zero (1)
- Neutron Science (6)
- Nuclear Energy (3)
- Physics (3)
- Polymers (2)
- Quantum Computing (14)
- Quantum Science (13)
- Security (1)
- Simulation (11)
- Software (1)
- Space Exploration (2)
- Summit (27)
- Sustainable Energy (4)
- Transportation (4)
Media Contacts
![An artist rendering of the SKA’s low-frequency, cone-shaped antennas in Western Australia. Credit: SKA Project Office.](/sites/default/files/styles/list_page_thumbnail/public/2019-12/SKA1_AU_closeup_midres_0.jpg?h=2e9e19b1&itok=jNXmboXl)
For nearly three decades, scientists and engineers across the globe have worked on the Square Kilometre Array (SKA), a project focused on designing and building the world’s largest radio telescope. Although the SKA will collect enormous amounts of precise astronomical data in record time, scientific breakthroughs will only be possible with systems able to efficiently process that data.
![The students analyzed diatom images like this one to compare wild and genetically modified strains of these organisms. Credit: Alison Pawlicki/Oak Ridge National Laboratory, US Department of Energy.](/sites/default/files/styles/list_page_thumbnail/public/2019-11/RI4362007.png?h=37702503&itok=9lQReLRe)
Students often participate in internships and receive formal training in their chosen career fields during college, but some pursue professional development opportunities even earlier.
![Misha Krassovski, a computer scientist at Oak Ridge National Laboratory, stands in front of the Polarstern, a 400-foot long German icebreaker. Krassovski lived aboard the Polarstern during the first leg of the MOSAiC mission, the largest polar expedition ever. Credit: Misha Krassovski/Oak Ridge National Laboratory, U.S. Dept. of Energy](/sites/default/files/styles/list_page_thumbnail/public/2019-10/IMG_0851_large.jpg?h=0d27ee61&itok=SDcaxULh)
In the vast frozen whiteness of the central Arctic, the Polarstern, a German research vessel, has settled into the ice for a yearlong float.
![Heat impact map](/sites/default/files/styles/list_page_thumbnail/public/2019-07/Winter_HDD_Change_ORNL.gif?h=e87b941e&itok=8t83D_u_)
A detailed study by Oak Ridge National Laboratory estimated how much more—or less—energy United States residents might consume by 2050 relative to predicted shifts in seasonal weather patterns
![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.
![Arjun Shankar Arjun Shankar](/sites/default/files/styles/list_page_thumbnail/public/shankar.png?itok=qqOR_eUI)
The field of “Big Data” has exploded in the blink of an eye, growing exponentially into almost every branch of science in just a few decades. Sectors such as energy, manufacturing, healthcare and many others depend on scalable data processing and analysis for continued in...