Filter News
Area of Research
- (-) Biology and Environment (58)
- (-) Clean Energy (57)
- Advanced Manufacturing (7)
- Biology and Soft Matter (1)
- Building Technologies (1)
- Computational Biology (2)
- Computational Engineering (2)
- Computer Science (5)
- Electricity and Smart Grid (1)
- Functional Materials for Energy (1)
- Fusion and Fission (5)
- Isotopes (13)
- Materials (23)
- Materials for Computing (9)
- Mathematics (1)
- National Security (18)
- Neutron Science (12)
- Quantum information Science (2)
- Supercomputing (34)
News Topics
- (-) 3-D Printing/Advanced Manufacturing (31)
- (-) Big Data (5)
- (-) Biomedical (6)
- (-) Computer Science (12)
- (-) Cybersecurity (4)
- (-) Environment (63)
- (-) Mercury (4)
- (-) Space Exploration (1)
- Advanced Reactors (3)
- Artificial Intelligence (6)
- Bioenergy (28)
- Biology (48)
- Biotechnology (8)
- Buildings (24)
- Chemical Sciences (8)
- Clean Water (9)
- Climate Change (29)
- Composites (8)
- Coronavirus (5)
- Critical Materials (4)
- Decarbonization (25)
- Energy Storage (36)
- Exascale Computing (3)
- Fossil Energy (1)
- Frontier (3)
- Fusion (2)
- Grid (17)
- High-Performance Computing (12)
- Hydropower (6)
- Machine Learning (4)
- Materials (28)
- Materials Science (12)
- Mathematics (1)
- Microscopy (8)
- Nanotechnology (4)
- National Security (3)
- Net Zero (3)
- Neutron Science (4)
- Nuclear Energy (3)
- Partnerships (5)
- Polymers (6)
- Security (2)
- Simulation (2)
- Statistics (1)
- Summit (4)
- Sustainable Energy (51)
- Transformational Challenge Reactor (1)
- Transportation (25)
Media Contacts
A new deep-learning framework developed at ORNL is speeding up the process of inspecting additively manufactured metal parts using X-ray computed tomography, or CT, while increasing the accuracy of the results. The reduced costs for time, labor, maintenance and energy are expected to accelerate expansion of additive manufacturing, or 3D printing.
Millions of miles of pipelines and conduits across the United States make up an intricate network of waterways used for municipal, agricultural and industrial purposes.
Tomás Rush began studying the mysteries of fungi in fifth grade and spent his college intern days tromping through forests, swamps and agricultural lands searching for signs of fungal plant pathogens causing disease on host plants.
Researchers at ORNL have developed an online tool that offers industrial plants an easier way to track and download information about their energy footprint and carbon emissions.
ORNL researchers are deploying their broad expertise in climate data and modeling to create science-based mitigation strategies for cities stressed by climate change as part of two U.S. Department of Energy Urban Integrated Field Laboratory projects.
A crowd of investors and supporters turned out for last week’s Innovation Crossroads Showcase at the Knoxville Chamber as part of Innov865 Week. Sponsored by ORNL and the Tennessee Advanced Energy Business Council, the event celebrated deep-tech entrepreneurs and the Oak Ridge Corridor as a growing energy innovation hub for the nation.
ORNL has provided hydropower operators with new data to better prepare for extreme weather events and shifts in seasonal energy demands caused by climate change.
Two years after ORNL provided a model of nearly every building in America, commercial partners are using the tool for tasks ranging from designing energy-efficient buildings and cities to linking energy efficiency to real estate value and risk.
Global carbon emissions from inland waters such as lakes, rivers, streams and ponds are being undercounted by about 13% and will likely continue to rise given climate events and land use changes, ORNL scientists found.
Five technologies invented by scientists at the Department of Energy’s Oak Ridge National Laboratory have been selected for targeted investment through ORNL’s Technology Innovation Program.