Filter News
Area of Research
- (-) Supercomputing (83)
- Advanced Manufacturing (22)
- Biology and Environment (36)
- Building Technologies (1)
- Clean Energy (178)
- Climate and Environmental Systems (1)
- Computational Biology (2)
- Computational Engineering (2)
- Computer Science (8)
- Electricity and Smart Grid (3)
- Functional Materials for Energy (1)
- Fusion and Fission (7)
- Fusion Energy (2)
- Materials (46)
- Materials for Computing (9)
- National Security (24)
- Neutron Science (20)
- Nuclear Science and Technology (4)
- Quantum information Science (1)
- Sensors and Controls (1)
- Transportation Systems (2)
News Topics
- (-) 3-D Printing/Advanced Manufacturing (5)
- (-) Artificial Intelligence (36)
- (-) Grid (5)
- (-) Summit (43)
- (-) Transportation (6)
- Advanced Reactors (1)
- Big Data (20)
- Bioenergy (9)
- Biology (11)
- Biomedical (17)
- Biotechnology (2)
- Buildings (4)
- Chemical Sciences (5)
- Climate Change (17)
- Computer Science (95)
- Coronavirus (14)
- Critical Materials (3)
- Cybersecurity (8)
- Decarbonization (5)
- Energy Storage (8)
- Environment (21)
- Exascale Computing (24)
- Frontier (29)
- Fusion (1)
- High-Performance Computing (40)
- Isotopes (2)
- Machine Learning (14)
- Materials (15)
- Materials Science (16)
- Mathematics (1)
- Microscopy (7)
- Molten Salt (1)
- Nanotechnology (11)
- National Security (8)
- Net Zero (1)
- Neutron Science (13)
- Nuclear Energy (4)
- Partnerships (1)
- Physics (8)
- Polymers (2)
- Quantum Computing (19)
- Quantum Science (24)
- Security (5)
- Simulation (15)
- Software (1)
- Space Exploration (3)
- Sustainable Energy (10)
Media Contacts
University of Pennsylvania researchers called on computational systems biology expertise at Oak Ridge National Laboratory to analyze large datasets of single-cell RNA sequencing from skin samples afflicted with atopic dermatitis.
A study led by researchers at ORNL used the nation’s fastest supercomputer to close in on the answer to a central question of modern physics that could help conduct development of the next generation of energy technologies.
To explore the inner workings of severe acute respiratory syndrome coronavirus 2, or SARS-CoV-2, researchers from ORNL developed a novel technique.
A team of scientists led by the Department of Energy’s Oak Ridge National Laboratory and the Georgia Institute of Technology is using supercomputing and revolutionary deep learning tools to predict the structures and roles of thousands of proteins with unknown functions.
The U.S. Department of Energy’s Office of Science announced allocations of supercomputer access to 51 high-impact computational science projects for 2022 through its Innovative and Novel Computational Impact on Theory and Experiment, or INCITE, program.
The daily traffic congestion along the streets and interstate lanes of Chattanooga could be headed the way of the horse and buggy with help from ORNL researchers.
Improved data, models and analyses from ORNL scientists and many other researchers in the latest global climate assessment report provide new levels of certainty about what the future holds for the planet
An ORNL-led team comprising researchers from multiple DOE national laboratories is using artificial intelligence and computational screening techniques – in combination with experimental validation – to identify and design five promising drug therapy approaches to target the SARS-CoV-2 virus.
At the Department of Energy’s Oak Ridge National Laboratory, scientists use artificial intelligence, or AI, to accelerate the discovery and development of materials for energy and information technologies.
The Department of Energy’s Oak Ridge National Laboratory has licensed its award-winning artificial intelligence software system, the Multinode Evolutionary Neural Networks for Deep Learning, to General Motors for use in vehicle technology and design.