Filter News
Area of Research
- (-) Supercomputing (42)
- Advanced Manufacturing (4)
- Biology and Environment (45)
- Building Technologies (2)
- Clean Energy (92)
- Computational Biology (1)
- Computational Engineering (1)
- Computer Science (8)
- Electricity and Smart Grid (2)
- Energy Sciences (2)
- Fusion and Fission (20)
- Fusion Energy (11)
- Isotopes (1)
- Materials (36)
- Materials for Computing (12)
- National Security (20)
- Neutron Science (13)
- Nuclear Science and Technology (12)
- Quantum information Science (3)
- Sensors and Controls (1)
News Type
News Topics
- (-) Artificial Intelligence (22)
- (-) Coronavirus (9)
- (-) Energy Storage (2)
- (-) Fusion (1)
- (-) Grid (1)
- (-) Machine Learning (8)
- (-) Nanotechnology (6)
- (-) Simulation (11)
- (-) Sustainable Energy (4)
- 3-D Printing/Advanced Manufacturing (2)
- Advanced Reactors (1)
- Big Data (17)
- Bioenergy (3)
- Biology (7)
- Biomedical (11)
- Biotechnology (1)
- Buildings (2)
- Chemical Sciences (2)
- Climate Change (14)
- Computer Science (61)
- Critical Materials (3)
- Cybersecurity (2)
- Decarbonization (3)
- Environment (17)
- Exascale Computing (13)
- Frontier (14)
- High-Performance Computing (23)
- Materials (5)
- Materials Science (9)
- Mathematics (1)
- Microscopy (2)
- National Security (3)
- Net Zero (1)
- Neutron Science (6)
- Nuclear Energy (3)
- Physics (3)
- Polymers (2)
- Quantum Computing (14)
- Quantum Science (13)
- Security (1)
- Software (1)
- Space Exploration (2)
- Summit (27)
- Transportation (4)
Media Contacts
A study by researchers at the ORNL takes a fresh look at what could become the first step toward a new generation of solar batteries.
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.
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.
Twenty-seven ORNL researchers Zoomed into 11 middle schools across Tennessee during the annual Engineers Week in February. East Tennessee schools throughout Oak Ridge and Roane, Sevier, Blount and Loudon counties participated, with three West Tennessee schools joining in.
To better understand the spread of SARS-CoV-2, the virus that causes COVID-19, Oak Ridge National Laboratory researchers have harnessed the power of supercomputers to accurately model the spike protein that binds the novel coronavirus to a human cell receptor.
A multi-institutional team, led by a group of investigators at Oak Ridge National Laboratory, has been studying various SARS-CoV-2 protein targets, including the virus’s main protease. The feat has earned the team a finalist nomination for the Association of Computing Machinery, or ACM, Gordon Bell Special Prize for High Performance Computing-Based COVID-19 Research.
ORNL and three partnering institutions have received $4.2 million over three years to apply artificial intelligence to the advancement of complex systems in which human decision making could be enhanced via technology.
ORNL researchers have developed an intelligent power electronic inverter platform that can connect locally sited energy resources such as solar panels, energy storage and electric vehicles and smoothly interact with the utility power grid.